COMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT REPORT Accompanying the document Proposal for a Directive of the European Parliament and of the Council amending Directive 2010/40/EU of the European Parliament and of the Council of 7 July 2010 on the framework for the deployment of Intelligent Transport Systems in the field of road transport and for interfaces with other modes of transport

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https://www.ft.dk/samling/20211/kommissionsforslag/kom(2021)0813/forslag/1840530/2502445.pdf

EN EN
EUROPEAN
COMMISSION
Strasbourg, 14.12.2021
SWD(2021) 474 final
COMMISSION STAFF WORKING DOCUMENT
IMPACT ASSESSMENT REPORT
Accompanying the document
Proposal for a Directive of the European Parliament and of the Council
amending Directive 2010/40/EU of the European Parliament and of the Council of 7 July
2010 on the framework for the deployment of Intelligent Transport Systems in the field
of road transport and for interfaces with other modes of transport
{COM(2021) 813 final} - {SEC(2021) 436 final} - {SWD(2021) 475 final}
Offentligt
KOM (2021) 0813 - SWD-dokument
Europaudvalget 2021
i
Table of contents
1. INTRODUCTION .................................................................................................................................1
1.1. POLITICAL CONTEXT .......................................................................................................................1
1.2. LEGAL AND POLICY CONTEXT......................................................................................................3
1.3. EVALUATION OF THE EXISTING DIRECTIVE..............................................................................5
2. PROBLEM DEFINITION .....................................................................................................................7
2.1. WHAT IS THE PROBLEM?.................................................................................................................7
2.2. WHAT ARE THE PROBLEM DRIVERS? ..........................................................................................9
2.2.1. DRIVER A: LACK OF INTEROPERABILITY AND CONTINUITY OF APPLICATIONS, SYSTEMS
AND SERVICES HINDERS THE DEVELOPMENT OF A COMMON ITS MARKET..................10
2.2.2. DRIVER B: LACK OF CONCERTATION AND EFFECTIVE STAKEHOLDER COORDINATION
.............................................................................................................................................................12
2.2.3. DRIVER C: LIMITED DATA AVAILABILITY AND ACCESS, LACK OF DATA QUALITY AND
LIMITED EXCHANGE AND USAGE OF DATA ............................................................................14
2.3. How will the problem evolve? .................................................................................................17
3. WHY SHOULD THE EU ACT? .........................................................................................................19
3.1. Legal basis................................................................................................................................19
3.2. Subsidiarity: Necessity of EU action........................................................................................19
3.3. Subsidiarity: Added value of EU action...................................................................................20
4. OBJECTIVES: WHAT IS TO BE ACHIEVED? ................................................................................20
4.1. General objectives....................................................................................................................20
4.2. Specific objectives ...................................................................................................................20
5. WHAT ARE THE AVAILABLE POLICY OPTIONS? .....................................................................22
5.1. What is the baseline from which options are assessed? ...........................................................22
5.2. Description of retained policy measures ..................................................................................26
5.2.1. Measures discarded at an early stage .......................................................................................30
5.2.2. Retained policy measures and policy options overview...........................................................32
5.3. Description of the policy options .............................................................................................33
5.3.1. PO1: Strengthened coordination and deployment principles ...................................................34
5.3.2. PO2: Mandate collection and availability of crucial data.........................................................35
5.3.3. PO3: Mandate provision of essential services..........................................................................35
6. WHAT ARE THE IMPACTS OF THE POLICY OPTIONS?............................................................36
6.1. Economic impacts ....................................................................................................................36
6.2. Social impacts ..........................................................................................................................42
6.3. Environmental impacts.............................................................................................................45
7. HOW DO THE OPTIONS COMPARE?.............................................................................................48
7.1. Effectiveness ............................................................................................................................48
7.2. Efficiency.................................................................................................................................49
7.3. Coherence.................................................................................................................................51
7.4. Proportionality..........................................................................................................................52
7.5. Summary of comparison of options, including stakeholder views...........................................52
7.6. Sensitivity analysis...................................................................................................................53
8. PREFERRED OPTION .......................................................................................................................56
ii
8.1. Policy option 3: Mandating provision of essential services .....................................................56
8.2. REFIT (simplification and improved efficiency) .....................................................................57
9. HOW WILL ACTUAL IMPACTS BE MONITORED AND EVALUATED? ..................................57
ANNEX 1: PROCEDURAL INFORMATION.............................................................................................59
1. LEAD DG, DECIDE PLANNING/CWP REFERENCES...................................................................59
2. ORGANISATION AND TIMING ......................................................................................................59
3. CONSULTATION OF THE RSB .......................................................................................................59
4. EVIDENCE, SOURCES AND QUALITY .........................................................................................59
ANNEX 2: STAKEHOLDER CONSULTATION .......................................................................................61
1. INTRODUCTION ...............................................................................................................................61
2. CONSULTATION METHODS...........................................................................................................62
ANNEX 3: WHO IS AFFECTED AND HOW? ...........................................................................................67
1. PRACTICAL IMPLICATIONS OF THE INITIATIVE .....................................................................67
2. SUMMARY OF COSTS AND BENEFITS ........................................................................................67
ANNEX 4: ANALYTICAL METHODS ......................................................................................................70
1. DESCRIPTION OF THE MODELLING TOOL USED .....................................................................70
2. BASELINE SCENARIO .....................................................................................................................78
3. ASSUMPTIONS ON THE ITS DEPLOYMENT IN THE POLICY OPTIONS.................................89
4. ASSUMPTIONS ON ITS SERVICE COST DATA ...........................................................................91
5. PRIMARY INPUT DATA.................................................................................................................105
5.1. Bundle 1a- Multimodal travel information service ................................................................105
5.2. Bundle 1a - Multimodal travel information and booking/re-selling service (MaaS)..............108
5.3. Bundle 1b - Travel Information Service (Road).....................................................................110
5.4. Bundle 1b - Real-time traffic information service..................................................................112
5.5. Bundle 1b - Parking and pricing information.........................................................................115
5.6. Bundle 1b - Recharging/refuelling location and pricing information.....................................117
5.7. Bundle 2 - Traffic network management systems..................................................................118
5.8. Bundle 2 – Mobility Management systems............................................................................122
5.9. Bundle 3 - Road safety-related minimum universal traffic information service ....................122
5.10. Bundle 3 - Safe and secure truck parking location information system .................................125
5.11. Bundle 3 - Safe and secure truck parking location reservation system ..................................127
5.12. Bundle 4 – Vehicle-to-Vehicle (V2V) C-ITS services...........................................................128
5.12.1. Emergency electronic brake light (EBL) ........................................................128
5.12.2. Emergency vehicle approaching (EVA) .........................................................132
5.12.3. Slow or stationary vehicle(s) warning (SSV) .................................................133
5.12.4. Traffic jam ahead warning (TJW) ..................................................................137
5.12.5. Hazardous location notification (HLN) ..........................................................142
5.13. Bundle 5 - C-ITS V2I motorway focused applications ..........................................................146
5.13.1. In-vehicle signage (VSGN) ............................................................................146
5.13.2. In-vehicle speed limits (VSPD)......................................................................148
5.13.3. Probe Vehicle Data (PVD) .............................................................................152
5.13.4. Roadworks warning (RWW) ..........................................................................154
5.13.5. Weather conditions (WTC).............................................................................157
5.13.6. Shockwave damping (SWD) ..........................................................................161
5.14. Bundle 5 - C-ITS V2I urban only applications ......................................................................162
iii
5.14.1. Green Light Optimal Speed Advisory (GLOSA) / Time to Green (TTG)......162
5.14.2. Signal violation/Intersection safety (SigV).....................................................166
5.14.3. Traffic signal priority request by designated vehicles (TSP)..........................168
5.15. Bundle 6 - Vulnerable road user protection – pedestrians and cyclists (VRU)......................170
5.16. Bundle 6 – Cooperative Adaptive Cruise Control..................................................................171
5.17. Bundle 6 – Other ....................................................................................................................172
6. OVERLAP BETWEEN SERVICES .................................................................................................172
Glossary
Term or acronym Meaning or definition
ASTRA ASsessment of TRAnsport Strategies (modelling tool)
CAV Connected and Automated Vehicle
CCAM Cooperative, Connected and Automated Mobility
CEF Connecting Europe Facility
C-ITS Cooperative Intelligent Transport System
CO2 Carbon Dioxide
Day 1 Mature C-ITS services (deployed)
Day 1.5 Close to mature C-ITS services (partially deployed)
Day 2 C-ITS services under development (not yet deployed)
Day 3 Future (automation support) C-ITS services
eCall Automated 112-based in-vehicle emergency call system
EU CCMS EU C-ITS Security Credential Management System
GDPR General Data Protection Regulation
GLOSA Green Light Optimal Speed Advisory
IIA Inception Impact Assessment
ITS Intelligent Transport System
KPI Key Performance Indicator
LNG Liquefied Natural Gas
MaaS Mobility as a Service
MDM Multimodal Digital Mobility
MMTIS Multi Modal Travel Information Service
MS Member State
NAP National Access Point
NOx Nitrogen oxides
iv
OEM Original Equipment Manufacturer
OPC Open Public Consultation
PM Particulate Matter
PND Personal Navigation Device
PO Policy Option
PRM Person with Reduced Mobility
RSI Road Side Infrastructure (supporting ITS)
RSU Road Side Unit (supporting C-ITS)
RTTI Real-Time Traffic Information
S&S Safe and secure
SME Small or Medium Enterprise
SRTI Safety Related Traffic Information
SSMS Sustainable and Smart Mobility Strategy
SUMP Sustainable Urban Mobility Plan
TMC Traffic management centre
TRUST TRansport eUropean Simulation Tool (modelling tool)
UVAR Urban Vehicle Access Restrictions
V2I Vehicle to Infrastructure
V2V Vehicle to Vehicle
VMS Variable Message Sign
VOC Volatile Organic Compound
VRU Vulnerable Road Users
1
1. INTRODUCTION
1.1. Political context
The Commission’s Communication on a Sustainable and Smart Mobility Strategy (SSMS)1
puts forward a fundamental transformation of the European transport system to achieve the
objective of a sustainable, smart and resilient mobility. The strategy is clear: in order to make
transport truly more sustainable we need to deliver effective multi-modality, using the most
efficient mode for each leg of the journey. In addition, each mode needs to become more
efficient; for road this means that shared solutions increasingly provide a viable alternative for
private vehicle ownership. Digitalisation is an indispensable driver to making the entire system
seamless and more efficient, as well as further increasing the levels of safety, security,
reliability, and comfort. The Strategy identifies the deployment of Intelligent Transport
Systems (ITS) as a key action in achieving a connected and automated multimodal mobility.
The latter combines new developments such as Mobility as a Service (MaaS) and Cooperative,
Connected and Automated Mobility (CCAM). CCAM transforms a driver into a user of a
shared fleet of vehicles, fully integrated in a multi-modal transport system, made seamless by
Multimodal Digital Mobility (MDM) services such as MaaS. ITS deployment has the potential
to improve significantly the functioning of the whole transport system as they better inform
transport users and enable them to make safer, more coordinated and ‘smarter’ use of transport
networks.
The SSMS reaffirmed that the death toll for all modes of transport in the EU should be close
to zero by 20502
. Cooperative Intelligent Transport Systems (C-ITS)3
, which allow vehicles,
transport infrastructure and other road users to communicate and coordinate their actions, have
an important role in the next steps towards Vision Zero4
. Building on existing synergies (such
as eCall) with the General Safety Regulation5
ITS will increasingly complement and provide
support to advanced driver assistance systems (e.g. Intelligent Speed Assistance (ISA)). This
will mark a move from passive and active safety, to cooperative safety, and is expected to bring
a much needed step-change to bring evolutions in road fatalities back on track.
The Commission’s Communication on a European Strategy for Data6
recognizes that data-
driven innovation will bring enormous benefits for citizens through its contribution to the
Green Deal, as well as help making Europe fit for the digital age. It announced the revision of
the ITS Directive, including some of its delegated regulations, as well as the intention to
establish in 2021 a stronger coordination mechanism for the National Access Points (NAPs)7
established under the ITS Directive through an EU-wide CEF Programme Support Action.
1
COM(2020)789 final
2
COM(2011)144 final
3
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52016DC0766
4
https://ec.europa.eu/transport/road_safety/sites/default/files/move-2019-01178-01-00-en-tra-00_3.pdf
5
https://eur-lex.europa.eu/eli/reg/2019/2144/oj
6
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020DC0066
7
https://ec.europa.eu/transport/themes/its/road/action_plan/nap_en
2
Improved functioning of the entire transport system is a key element to deliver a 90% reduction
in the transport sector emissions by 2050, a target needed to achieve climate neutrality. The
European Green Deal8
is the new growth strategy for Europe by placing climate action at the
core of the EU’s policies and the European Parliament and the Council have found a provisional
political agreement on the European Climate Law9
, setting into law the objective of a climate-
neutral EU by 2050 and of the collective net greenhouse gas emission reduction target of at
least 55% below 1990 levels by 2030. On 14 July 2021 the Commission adopted a package of
proposals, “the Fit for 55 package”, to achieve this target.10
This revision will complement that
ambitious package by fostering connected and automated multimodal mobility. This also
fosters the uptake of zero-emission vehicles as in the future, based on fully interoperable data
underpinning new mobility services, a user will have a whole fleet at his/her disposal. Anxiety
about range or purchase cost is then mitigated, especially when that fleet can go recharge itself
automatically. In other words, emerging ITS services could not only accelerate the uptake of
zero-emission vehicles but also help use them more efficiently. Finally, smoothening road
traffic flows (noting that zero-emission fleets should not lead to zero-emission traffic jams)
will bring a smaller contribution. Such improvements come with (small) rebound effects, i.e.
more efficient traffic may lead to some more traffic. This is however not an argument against
efficient traffic; it does highlight that we need flanking measures to decouple the amount of
traffic we want from the efficiency of remaining traffic. Ideally, shared zero emission vehicles
function as feeder services to existing and even more efficient modes, for both passengers and
freight, providing for seamless and more inclusive travel.
ITS and C-ITS, combined with advances in automated vehicle technologies, are not just strong
enablers but an integral part of CCAM services. Europe is still leading (37% of patent
applications) but countries around the world (e.g. US, Japan, Korea and China) are moving
rapidly towards developing and deploying digital technologies in road transport 11
. The
accelerated deployment of ITS and C-ITS would give the European automotive and ITS
industry an advantage, leading to higher levels of new business opportunities and job creation,
and more significant research and innovation impacts. As the jobs of millions of Europeans
depend directly or indirectly on the automotive industry (12 million people, accounting for 4%
of GDP)12
, it is critical that the sector is provided with the conditions to keep up with global
market players.
This impact assessment (IA) accompanies a legislative proposal for the revision of Directive
2010/40/EU on the framework for the deployment of Intelligent Transport Systems in the field
of road transport and for interfaces with other modes of transport13
, amended as regards the
period for adopting delegated acts 14
. The deployment of ITS can make an important
contribution to the Commission priorities, in particular to the European Green Deal and making
8
COM(2019)640 final
9
https://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1588581905912&uri=CELEX:52020PC0080
10
https://ec.europa.eu/commission/presscorner/detail/en/IP_21_3541
11
https://www.epo.org/news-events/news/2018/20181106.html
12
https://ec.europa.eu/growth/sectors/automotive_en
13
Directive 2010/40/EU, OJ L 207, 6.8.2010, p. 1–13.
14
Decision (EU) 2017/2380, OJ L 340, 20.12.2017, p. 1–3
3
Europe fit for the digital age. It is part of a package of legislative initiatives aiming at
contributing to the goals of decarbonisation, digitalisation and higher resilience of transport
infrastructure. Next to the revision of the ITS Directive, there will be the review of the TEN-T
Regulation and the urban mobility package, also considering new provisions relating to ITS.
1.2. Legal and policy context
ITS apply information and communication technologies to transport to share transport data and
information with all transport users (road authorities, public transport operators, businesses,
citizens, etc.). ITS help to significantly improve road safety and traffic efficiency by helping
transport users to take better decisions and adapt to the traffic situation (e.g. slow down for
dangerous situations, adapt speed to ensure green light, avoid congested areas, etc.). ITS help
to better use existing infrastructure, multimodality options and enhance traffic management.
The ITS Directive establishes a framework to support the coordinated and coherent deployment
of ITS in the road sector and its interfaces with other modes of transport (e.g. multimodal
journey planners combining road and rail). It also ensures interoperability and fosters
continuity of services (i.e. it always works, for all users, everywhere) while leaving Member
States the freedom to decide which ITS services to invest in. The ITS Directive provides for
developing specifications (the detailed requirements needed to ensure the objectives of the
Directive) in four priority areas, a description of which is provided in Annex 1 of the Directive
and summarised in Table 1 below. In addition, six sets of requirements are identified as priority
actions. The Directive foresees reporting by Member States every three years on all priority
areas, complemented by reporting requirements in Delegated Regulations.
Table 1: Priority areas and priority actions
Priority area I:
Optimal use of road,
traffic and travel
data
 priority action (a) requirements to make EU-wide multimodal travel information
services (MMTIS) accurate and available across borders to ITS users
 priority action (b) requirements to make EU-wide real-time traffic information
(RTTI) services accurate and available across borders to ITS users
 requirements for the collection by relevant public authorities and/or, where relevant,
by the private sector of road and traffic data and making it available to service
providers
 priority action (c) requirements for the road safety related ‘universal traffic
information’ (SRTI) provided, where possible, free of charge to all users
Priority area II:
Continuity of traffic
and freight
management ITS
services
 develop an EU ITS Framework Architecture
 requirements for the continuity of ITS services, in particular for cross-border
passenger and freight services
 requirements for ITS applications (notably the tracking and tracing of freight along
its journey and across modes of transport) for freight transport logistics
 interfaces to ensure interoperability and compatibility between the urban ITS
architecture and the European ITS architecture
Priority area III:
ITS road safety and
 priority action (d) measures for the harmonised provision of an interoperable EU-
wide eCall
4
security
applications
 priority action (e) measures to provide information services for safe and secure
(S&S) parking places for trucks and commercial vehicles
 priority action (f) measures to provide reservation services for safe and secure
(S&S) parking places for trucks and commercial vehicles
Priority area IV:
Linking the vehicle
with the transport
infrastructure
 measures to integrate different ITS applications on an open in-vehicle platform
 measures to progress the development and implementation of cooperative (vehicle-
vehicle, vehicle-infrastructure, infrastructure-infrastructure) systems
So far five priority actions resulted in supplementing the Directive by a Commission Delegated
Regulation (a, b, c, d and e). Regarding the provision of reservation services for safe and secure
(S&S) parking places for trucks and commercial vehicles (priority action f), the Commission
conducted several consultations with Member State experts and the main stakeholders, which
led to the conclusion that there was no need for specifications and standards on reservation of
parking areas. Four Commission Delegated Regulations ask for setting up a national access
point, establishing a single access point for ITS users to discover ITS data and foster its sharing
and re-use (related to priority actions a, b, c and e). A delegated regulation on C-ITS was
adopted under priority area IV but never entered into force following an objection by Council.15
Synergies with other EU policy instruments
For in-vehicle emergency calls to 112 (eCall) a Delegated Regulation16
under the ITS Directive
combines with a specific legislative framework for the mandatory equipment of vehicles in
Regulation (EU) 2015/75817
. Such synergies are expected to increase in the area of CCAM, for
example on ISA as defined in the General Safety Regulation18
and on C-ITS19
. The ITS
Directive also has synergies with the new road safety policy framework for 2020-203020
and
the legislative initiatives on vehicle and pedestrian safety21
and on infrastructure safety
management22
, all of which provide complementary provision to increase road safety.
Digitalisation is an important aspect of the revision of the TEN-T Regulation. Road users on
the TEN-T network must benefit from the opportunities offered by developments on data
collection and ITS services to increase their safety. Therefore, a provision has been added to
the Regulation to ensure safety-related events are detected for re-use in safety-related traffic
information services, in line with Delegated Regulation 886/2013 under the ITS Directive.
As specific legislation, expertise and programme support actions on alternative fuels
infrastructure are in place, discussions on the relevant data types are (also) held within the
Alternative Fuels Infrastructure Regulation (AFIR) framework.23
To ensure complementarity
15
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=PI_COM%3AC%282019%291789
16
https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=celex%3A32013R0305
17
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:32015R0758
18
https://eur-lex.europa.eu/eli/reg/2019/2144/oj
19
https://eur-lex.europa.eu/legal-content/EN/PIN/?uri=PI_COM%3AC%282019%291789
20
https://op.europa.eu/en/publication-detail/-/publication/d7ee4b58-4bc5-11ea-8aa5-01aa75ed71a1
21
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52018PC0286
22
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52018PC0274
23
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52021PC0559
5
and transparency with the ITS Directive, it has been proposed that the AFIR covers the mandate
to make data available for the related data types and further specify the data requirements. To
ensure AFIR data is made accessible on the NAPs in a standardised format, a reference to
Delegated Regulation 2015/962 under the ITS Directive is made.
Most ITS data is not personal (e.g. speed limits, traffic rules, maps) but some personal data is
needed for some critical road safety services (e.g. vehicles sharing they are braking hard warn
oncoming traffic of a potentially dangerous situation). Despite measures such as anonymization
and data aggregation, data generated through the usage of vehicles can be considered personal
and in those cases the General Data Protection Regulation (GDPR)24
applies.
The upcoming multimodal digital mobility (MDM) services initiative announced in the SSMS
aims at increasing the deployment and operational use of MDM services within and across
modes, to significantly improve multimodality, inclusiveness and sustainability. In view of
identified market imbalances and difficulties to share commercially sensitive data, this
proposal seeks to address market challenges hampering the development of MDM services and
to establish a framework for commercial agreement for services reselling mobility products.
The provisions of the Platform to Business (P2B) Regulation25
are applicable to several ITS
service providers, such as MaaS applications which offer services to consumers in the EU, and
impose more transparency obligations to platforms in relation to the access that business users
may have to data (personal or not) when using the platform. The forthcoming Digital Markets
Act and Data Governance Act, part of the EU’s Digital Strategy may have synergies with the
ITS Directive notably in the field of Business to Government (B2G) data sharing. Data made
accessible under the Delegated Acts under the ITS Directive is also expected to be part of the
future initiative on a common European mobility data space. This initiative aims to facilitate
the access, pooling and sharing of data from existing mobility and transport databases.
1.3. Evaluation of the existing Directive
The evaluation26
of the ITS Directive 2010/40/EU concluded that it had overall positive
impacts on the deployment of ITS across the EU and Member States. Despite this, the
evaluation identified shortcomings leading to 1) lack of coordination in ITS deployment across
the EU and 2) slow, risky and not-cost-effective ITS deployment. In consequence, ITS
deployment, despite improvements, still often remains restricted to a limited geographical
scope. Thus, there remains a clear need for further action at EU level on interoperability,
cooperation and data sharing to enable seamless, continuous ITS services across the EU, the
evaluation concluded. Stakeholders responded strongly positive on the relevance of the
delegated acts adopted under the Directive, however a few considered that some delegated acts
24
https://eur-lex.europa.eu/eli/reg/2016/679/oj
25
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32019R1150
26
https://ec.europa.eu/transport/sites/default/files/legislation/swd20190368-its-ex-post-evaluation.pdf
6
could be extended to further increase their relevance. This has been reflected in the Directive’s
updated working programme adopted on 11 December 201827
.
Member states reported progress in all priority areas, notably area IV, which was lagging
behind, now witnesses the emergence of many pilot projects for C-ITS, following actions to
establish a common legal and technical framework in order to ensure interoperability and
continuity at EU level.28
To make progress the EU level is still considered the most relevant
for providing such a framework to foster deployment. The main conclusions from the ex-post
evaluation, and their links with this impact assessment are presented in Table 2.
Table 2: Links between conclusions of the ex-post evaluation and the impact assessment
Main ex post evaluation conclusions Impact Assessment
Conclusions on relevance
The issues and challenges identified at the time of the
adoption as well as the general and specific objectives of the
Directive are still applicable.
The IA further develops the general and
specific objectives of the directive
Conclusions on effectiveness
The directive has had a positive but relatively limited
contribution towards the uptake of ITS. NAPs have been
established in many Member States since the adoption of the
delegated regulations, but the usage of the data provided by
NAPs is still relatively low, and only a limited number of
interoperable ITS services have been deployed so far.
Policy measures are defined to enlarge
the scope and further strengthen
investments in ITS and ensure the
deployment of essential services.
The ITS coordination mechanisms appear to have played a
positive role. Engagement with national authorities (via the
ITS Committee and the Expert Group) has worked well.
Interaction with other stakeholders through the ITS Advisory
Group has not been as successful.
Policy measures are defined to further
strengthen the coordination mechanisms
and involvement of all ITS stakeholders
Despite legislation in place, reluctance to share data continues
to be a limiting factor. This is due to issues of trust, high
expected costs and unclear benefits for those providing the
data
Policy measures are defined to increase
the availability of crucial data
Conclusions on efficiency
Benefits of ITS cannot yet be quantified but stakeholders see
costs as proportional and expect the benefits to outweigh the
costs in the long term when services and their use are scaled
up, if they should not do so already.
Policy measures are foreseen to increase
the deployment of ITS and reach the
scale needed to reap the (large) potential
benefits
The cost-effectiveness of reporting obligations is hampered
by the lack of comparability between Member State reports
(differences in structure, level of detail and use of KPIs)
Policy measures are foreseen to
harmonize all reporting obligations and
increase the use of KPIs
Conclusions on coherence and coordination
The ITS Directive and its delegated acts are internally
coherent, but the frequency and timing of reporting
obligations are currently not aligned. References between the
ITS Directive and other relevant EU legislation are
increasing, without introducing overlapping requirements.
This interdependence is expected to increase moving forward
to CCAM, on issues related to vehicles, telecommunications,
cybersecurity, liability and the processing and availability of
(personal) data
The IA includes measures to align
reporting requirements and address
synergies with other EU legislation,
mainly linked to the use of in-vehicle
data, bringing the GDPR into scope but
also synergies with existing requirements
for advanced driver assistance systems
and road infrastructure
Conclusions on EU added Value
EU level intervention brought benefits not possible with
action at national or local level alone. The need for EU action
The IA concludes that EU action
continues to be needed to deliver on the
27
https://ec.europa.eu/transport/sites/transport/files/legislation/c20188264_en.pdf
28
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=SWD%3A2019%3A373%3AFIN
7
Main ex post evaluation conclusions Impact Assessment
to address the key problem of incoherent, inconsistent and
fragmented development of ITS across the EU increased.
policy objectives.
2. PROBLEM DEFINITION
2.1. What is the problem?
Building on the evaluation of the ITS Directive, this IA further corroborated the problem
analysis through desk research and stakeholders participating in exploratory interviews and
workshops. The main problem is the “slow and fragmented deployment of ITS services,
hampering also the uptake of emerging ITS services”. Beyond TEN-T and including urban
areas (Member States are free to choose which sections of their road network they want to
cover) deployment remains slow and fragmented. ITS services cover many different aspects of
(road) transport but they all aim at improving road safety or at improving transport efficiency.
The latter includes linking all transport modes to foster a more sustainable and more inclusive
multi-modal transport system, also for people with reduced mobility. In addition, market
development in areas that are key for future transport competitiveness and growth is hampered,
including CCAM and MaaS. These are expected to be key enablers in the transition to a
mobility system that combines shared door-to-door mobility with public transport, using the
most effective mode for each leg of the journey, and help break the paradigm of private car
ownership.29
An overview of the drivers and consequences of this problem is presented in
Table 3.
Table 3: Overview of drivers, problems and implications
Drivers Problems Consequences
Lack of interoperability and continuity of
applications, systems and services hinders
the development of a common ITS market
Slow and
fragmented
deployment
of ITS
services,
hampering
also the
uptake of
emerging
ITS
services
Limited usage of ITS services with negative
impacts on road safety, congestion and transport
system efficiency, GHG and pollutant reduction
Lack of concertation and effective
stakeholder coordination
Limited development of services such as MaaS
and CCAM, leading to missed opportunities to
build an inclusive multi-modal transport system
Limited data availability and access, lack
of data quality and limited exchange and
usage of data
Limited internal market development (for
vehicles and infrastructure), limited competition
and consumer choice
The Commission’s evaluation of the ITS Directive indicated that many of the actions set out
in the ITS action plan and the priority actions identified in the Directive have been completed.
Table 4 outlines progress made across each priority area, as reported in the 2019 Commission
29
https://english.kimnet.nl/publications/documents-research-publications/2019/08/15/promising-groups-for-
mobility-as-a-service-in-the-netherlands
8
report to the Parliament and Council30
. As of June 2021, all Member States have set up NAPs31
,
enabling data sharing for the different specifications of the ITS Directive. The Member State
reports on the implementation of the Directive paint a picture of incomplete deployment of ITS
services and infrastructure and availability of relevant data along the different road types within
Member States, with deployment taking up predominantly within the TEN-T network (core
and comprehensive). Moreover, where Key Performance Indicators (KPI)32
on deployment are
reported33
, they highlight the uneven deployment of various ITS services. In the comprehensive
TEN-T network, a relatively high coverage is identified – considering this is voluntary
deployment – by ITS information-gathering infrastructure (57% for 14 Member States) and
RTTI data (75% for 14 MSs) and to a lesser extent traffic management and control (18% for
11 MSs) and automatic incident identification (24% for 13 MSs).
Table 4: Summary of Member States progress on implementing the Directive
Priority Area Member State Progress
I: Optimal use of
road, traffic and
travel data
Activities are ongoing across most MSs as 22 of the 24 EU MS that submitted a national
report, identified projects relevant to this priority area including EU funded projects.
MSs develop national journey planners and deploy data-collecting infrastructure. Some
challenges persist with engaging private sector operators in access to road safety data.
II: Continuity of
traffic and freight
management ITS
services
MSs are actively engaged, such as by improving their traffic management systems,
improving road-rail transport linkages and developing multimodal smart/e-ticketing for
public transport. 19 out of the 24 EU MS that submitted a report were actively involved
in at least one project in this area (including EU-funded projects).
III: ITS road
safety and security
applications
Aside from eCall and S&S truck parking, few activities have been reported. Due to their
focus on road safety, a few ITS projects along CEF corridors and the C-ITS deployment
activities can also be considered partly related to this priority area. 18 out of the 24 EU
MSs that submitted a report identified projects related to this priority area.
IV: Linking the
vehicle with the
transport
infrastructure
Considerable effort has been reported in this priority area, largely in relation to C-ITS.
20 MSs have been involved in pilot projects under the C-Roads Platform, with a focus
on building cross-border interoperability and harmonised standards. Most of these
projects are receiving funding from the Connected Europe Facility (CEF).
Source: Member State Reports (2020-2021)
The availability and accessibility of quality ITS data is a prerequisite for the deployment of all
ITS services and remains a serious issue. According to a JRC study34
, innovation deployment
in the area of CCAM, as well as in the area of low-carbon and shared mobility is significantly
lower as a consequence of the (slow) rate of investment in (ITS) infrastructure. The study
identifies a time delay of 10 to 20 years from the technical emergence of new solutions to their
30
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=SWD%3A2019%3A373%3AFIN
31
https://ec.europa.eu/transport/themes/its/road/action_plan/nap_en 21 MSs have NAPs for S&S parking
(priority action (e) – others have no S&S parking), 26 MS have one for MMTIS (priority action (a) – only
Bulgaria is lacking) and all 27 EU MS have them for SRTI (priority action (c)) and RTTI (priority action
(b))
32
KPI should be reported separately by type of road network / priority zone / transport network and nodes. List
of KPIs available on https://ec.europa.eu/transport/themes/its/road/action_plan/its_national_reports_en
33
Austria, Belgium, Denmark, Greece, Spain, Finland, Ireland, Italy, Latvia, the Netherlands, Poland, Romania,
Sweden and Norway
34
https://publications.jrc.ec.europa.eu/repository/handle/JRC116644
9
actual implementation and large-scale deployment. For instance, in 2016, a number of
manufacturers announced that vehicles of higher automation levels (SAE level 4 or 535
) would
be available as early as 2020-2021. This has not happened and release dates have been
postponed36
. Regardless, deployment is expected to vary significantly due to the availability of
(roadside and other) ITS infrastructure and data necessary for CCAM.37
As a result, even when
automated vehicles would be available, until the supporting ITS infrastructure is too, CCAM
services will not.
The deployment of MaaS is slow, some initiatives have been piloted across Europe but most
had problems reaching a significant scale and stable business operation replicable at the EU
level38
. Shortcomings of the implementation of the ITS Directive contribute to this as MaaS
requires relevant MMTIS data, currently available only to a limited extent.39
Additionally,
where MMTIS are developed, they are locally or regionally focused and not continuous across
larger geographical areas. Furthermore, the extent to which these mobility platforms will
integrate booking and payment services is uncertain. The deployment of (new) ITS services
with no harmonised specifications (such as mobility management services) is expected to lag
for a number of years and remain fragmented. Although such services are not explicitly
excluded from the current scope of the ITS Directive, they are also not clearly defined and
specifically targeted by existing priority actions and their deployment is slower and fragmented
as a result. Figure 1 shows that a clear majority of the stakeholders indicated that current
deployment levels of ITS services require further action in relation to the priority areas already
identified in the ITS Directive (priority areas I to IV), but also for emerging ITS services
(priority areas V to VII).
Figure 1: Stakeholder views on the need for EU action in existing and new priority areas
35
https://www.sae.org/news/2019/01/sae-updates-j3016-automated-driving-graphic
36
http://www.trt.it/wp/wp-content/uploads/2020/12/2021011_CAD_Employment_Impacts_Annexes.pdf
37
https://home.kpmg/uk/en/home/campaigns/2019/09/mobility-2030-future-of-mobility.html
38
https://cordis.europa.eu/project/id/723314
39
Only 8 Member States have reported an average of 52% availability of such multimodal data
10
2.2. What are the problem drivers?
All ITS, mature and emerging, depend on the - often bi-directional - exchange of data between
many stakeholders. That means that, despite the wide scope of services covered by the ITS
Directive, the problem drivers are common for all priority areas, namely:
 Driver A: Lack of interoperability and continuity of applications, systems and services
hinders the development of a common ITS market
 Driver B: Lack of concertation and effective stakeholder coordination
 Driver C: Limited data availability and access, lack of data quality and limited exchange
and usage of data
These problems drivers and their underlying factors are described in more detail below.
2.2.1. Driver A: Lack of interoperability and continuity of applications, systems and
services hinders the development of a common ITS market
A first contributing factor is financial and administrative capacity limitations. This is
highlighted in the KPIs for ITS deployment presented in the Member States country reports40
.
According to these, deployment of ITS services can vary significantly between countries, even
when comparing only the TEN-T network or motorways and the disparity between Member
States appears to be growing with some countries (e.g. Austria and Spain) having made
significantly greater progress than other countries (e.g. Latvia and Greece). Lack of
administrative and financial capacity is expected to continue delaying and fragmenting the
deployment of ITS services across the EU transport network without further EU level
intervention.41
Although several Member States receive funding for the creation of NAPs via
the Connecting Europe Facility (CEF)42
, this does not mean the full set of data types is available
on all NAPs. Several stakeholders43
pointed to the challenges with regard to collect, prepare
and share data on all road networks, especially for smaller cities.
This will likely also be the case for the deployment of services unreported so far, such as MaaS
applications. The mapping of such services reveals that deployment is highly localised and
driven by the private sector, resulting in the deployment of services with relatively limited
functional and geographic scope44
. Achieving the appropriate balance between public and
private components in a combined mobility scheme is a major issue, with actors needing to
compromise on different business roles and objectives within the same transport ecosystem.45
Barriers to interoperability and continuity of services also include lack of common standards,
principles and quality requirements for emerging ITS services. New service concepts such as
40
This has also been reported in the evaluation of the Directive.
41
https://ec.europa.eu/transport/sites/default/files/legislation/swd20190368-its-ex-post-evaluation.pdf
42
For MMTIS 17 MS receive CEF funding to help them develop their NAPs
43
UITP, POLIS, city of Hamburg
44
https://maas-alliance.eu/maas-in-action/
45
https://cordis.europa.eu/project/id/723314
11
MaaS and CCAM require the development of new common standards and priority actions if
they are to develop at scale across the EU, including on sharing data between road operators
and other stakeholders, speed limits, cycling networks, Urban Vehicle Access Restrictions
(UVAR), historical traffic data, roadworks in cities and other road and traffic specific rules.46
The majority of stakeholders responding to the Inception Impact Assessment referred to the
absence of interfaces that are able to link (all) essential vehicle data with (all) relevant ITS
service providers as the most important missing piece to support interoperability, scalability
and resilience of ITS services. The lack of interoperability and continuity of ITS services has
also been acknowledged as a key issue amongst the Open Public Consultation (OPC)
respondents as 42 out of 75 respondents participating to the survey indicated that they do not
know which systems are available in a given situation.
Figure 2: Survey responses regarding the relevance of Problem Driver A
Respondents to the targeted survey agreed to a large extent with the existence of Problem
Driver A for all types of ITS services as can be seen in Figure 2.
Finally, data generated by different transport modes also lacks interoperability, which is
especially relevant for services such as MMTIS and MaaS, as these integrate different transport
modes and modes of operation (including not only traditional modes such as road and public
transport, but also active modes and new mobility services such as shared and micro-mobility).
The 2016 Study on ITS Directive, Priority Action A: The Provision of EU-wide MMTIS
revealed that there is no single data exchange protocol for all transport modes, but rather one
per mode. This was identified as the primary issue to enable a level playing field for intermodal
services as the different data formats cannot be used by mobility platform providers and
46
Mentioned by stakeholders such as ASECAP, POLIS, EUROCITIES, EPF, FIA, MaaS alliance, 5GAA, city
of Lisbon, TomTom, Scania, Volkswagen Group
12
consumers.47
The European Platform for SUMPs underlined the need for the legal framework
to define interoperable architectures to ensure service availability to all users.48
2.2.2. Driver B: Lack of concertation and effective stakeholder coordination
A first contributing factor is the limited involvement and buy-in from external / industry
stakeholders through the existing cooperation mechanisms in the ITS governance
framework. The governance structure of the ITS Directive includes the following three bodies:
 The European ITS Committee (EIC)49
, composed of Member State representatives was
established through Article 15 of the Directive and is consulted on the working
programme, the reporting Guidelines, standardisation requests and non-binding
measures. It is also an important forum to facilitate the exchange of information with
Member States and develop an overall vision on ITS deployment in Europe.
 The European ITS Advisory Group (EIAG) was established according to Article 16 of
the Directive to advise the European Commission on business and technical aspects of
the deployment and use of ITS in the Union. The group is composed of high-level
representatives from a number of stakeholders, bringing together industry, users, social
partners, local authorities and other relevant parties.
 The ITS Member States Expert Group 50
composed of national experts that are
appointed by Member States to provide technical support in the development of the
delegated acts and subsequent monitoring of implementation. The Expert Group is
composed by different Member State experts depending on the topic of discussion.
This setting includes two higher level structures operating in parallel with the ITS Member
State Expert Group(s), which supports the preparation of the delegated acts and subsequent
monitoring. The ITS Advisory Group has convened three times formally, and another eight
times informally (when these meetings took place outside Brussels, mostly in conjunction with
ITS World or European Congresses). This included seven times with the members of the ITS
Committee, in the so-called “Friends of ITS” format. In addition, the ITS Advisory Group has
systematically been consulted in writing on the delegated acts, even if this was not formally
required in the Directive.
Whilst the format of the “Friends of ITS meeting” was generally well appreciated, as it allowed
open discussions with and between public and private stakeholders, the structure has not proven
to work effectively regarding the role of the ITS Advisory Group. Some members of the
Advisory Group have criticised specifically the timing of the involvement they have had via
this group as coming only at a very late stage of the regulatory preparation process, implying
they are informed, but not consulted on more strategic discussions, e.g. on the definition of the
work programmes and on the objectives of the new delegated acts. This may explain their
47
https://fsr.eui.eu/publications/?handle=1814/40685
48
https://www.eltis.org/sites/default/files/the_role_of_intelligent_transport_systems_its_in_sumps.pdf
49
https://ec.europa.eu/transparency/comitology-register/screen/committees/C39400/consult?lang=en
50
Register of Commission Expert Groups and Other Similar Entities, code number E01941
13
subsequently loss of interest in participating to the Advisory Group meetings. This has resulted
in lack of formal industry involvement in the implementation of the ITS work programme. This
is not due to lack of interest, as both public and private stakeholders increasingly recognise the
importance of coordinating priorities and investments when dealing with ITS. This was
demonstrated in the scope of the development of the Delegated acts, which included large
consultations of stakeholders to which many actively contributed. Also, within other related
Commission expert groups, such as those on eCall51
, C-ITS52
or CCAM53
, coordination with
industry stakeholders seemed to work better, which is related to the more upstream timing in
the policy development process.54
In the absence of their inclusion in the scope of the ITS Directive and a clear coordination
mechanism for the development of emerging services such as CCAM with all stakeholders,
leading to concrete cooperation, for example to coordinate the deployment of ITS-relevant
infrastructure, an uncoordinated deployment of ad hoc solutions is probable.55
Respondents to
the targeted survey agreed to a large extent with the existence of Problem Driver B as can be
seen in Figure 3.
Figure 3: Survey responses regarding the relevance of Problem Driver B
The lack of comparable monitoring of ITS deployment across the EU is another issue,
Member State reports do not help produce a comprehensive understanding of the current state
of deployment of ITS infrastructure and services. The analysis of 24 reports received in 2020-
2021 acknowledges that while most report on traffic management information, the majority
provided less information on most other ITS services. The reports are also not consistent
51
European eCall Implementation Platform - Register of Commission Expert Groups, code number E02481
52
Platform for the Deployment of C-ITS in the EU - Register of Commission Expert Groups, code number E03188
53
Expert group on CCAM - Register of Commission Expert Groups, code number E03657
54
The CCAM platform deals with R&I topics and does not directly involve stakeholders in the regulatory process
55
As mentioned by stakeholders such as ASECAP, ACEA and AustriaTech
14
regarding the level of detail used to monitor the deployment of ITS and the benefits produced
thereof. Specifically, only 17 Member State reports follow the proposed structure in line with
the four Priority Areas defined in the ITS Directive. The use of KPIs56
is even less consistent
as only 13 provide some sort of reporting on ITS deployment KPIs, 12 on benefit KPIs and 11
elaborate partially on financial KPIs. This leads to difficulties in mapping and supporting ITS
deployment across Member States, particularly for cross-border comparisons.
2.2.3. Driver C: Limited data availability and access, lack of data quality and
limited exchange and usage of data
A first contributing factor is long standing and emerging (trust) issues and issues related to
data protection, privacy and liability, linked to technological and legislative developments.
These were also cited in the evaluation of the ITS Directive as hindering the further deployment
of ITS services and are recurring issues as proven by the number of times the point has been
raised in different meetings of the ITS expert group57
over the last three years (see Figure 4).
Figure 4: Count of concerns raised in the ITS Expert Group meetings, 2017-2020
Source: produced by Ricardo E&E based on available meeting minutes. The red circles indicate topics that are
especially relevant to the problem drivers.
The Open Public Consultation (OPC) respondents supported this finding as stakeholders
participating to the survey (31 of 75), expressed concerns about the privacy and re-use of
personal data. To a lesser extent, concerns have also been expressed regarding the security of
ITS systems (18 of 75 participating stakeholders agreed with the issue). Concerns have also
56
List of KPIs available on https://ec.europa.eu/transport/themes/its/road/action_plan/its_national_reports_en
57
https://ec.europa.eu/transparency/regexpert/index.cfm?do=groupDetail.groupDetail&groupID=1941
15
been raised with regard to the security and privacy impacts of C-ITS which may slow down
wide-spread deployment. In their responses to the IIA, a range of stakeholders, including the
EPF, Move EU58
, the European Consumer Organisation (BEUC), ANEC59
and Eurocities
considered privacy and security concerns related to the sharing of static and dynamic transport
user and providers data. FIA identified the capacity of drivers to retain ownership of their data
as a key consideration for sharing. Other stakeholders also identified challenges to prove
alignment of the ITS Directive with the GDPR and ePrivacy legislations.60
The 2016 Study on ITS Directive, “Priority Action A: The Provision of EU-wide Multimodal
Travel Information Services” also revealed that the development of interoperable travel and
traffic data and their sharing and reuse is currently hindered by commercial confidentiality
issues. It highlighted again the need to increase trust in order to promote data sharing amongst
mobility stakeholders. In this respect, a set of common principles on the conditions of data
sharing and use of relevant data could increase stakeholder cooperation and the reuse of data.
The deployment of new types of services could pose new challenges in relation to existing
policies laying down data sharing, data protection and privacy, and liability requirements. The
development of the legal framework governing data protection61
since the ITS Directive came
into force might also lead to the need to align the provisions of the ITS Directive to clarify how
ITS services need to comply with data-related regulations and identify the conditions under
which data collection, sharing and reuse can be performed. The recent work of the European
Data Protection Board provides guidance to vehicle and equipment manufacturers, service
providers or any other data controller or processor to facilitate compliance with GDPR when
processing personal data in the context of connected vehicles and mobility related applications.
In addition to general recommendations, these Guidelines also analyse several examples of
data processing such as usage-based insurance or eCall. 62
Additionally, liability issues are still considered unresolved and can hinder the deployment of
ITS services. For example, in a study from 201863
the European Parliament noted the need to
revise the liability framework to address issues relevant to the deployment of automated
vehicles. Also, a JRC study on “The future of road transport - Implications of automated,
connected, low-carbon and shared mobility“ identified Connected and Automated Vehicles
(CAV) and other new mobility solutions as linked to raising issues in terms of privacy, and
equity. As CAVs utilise multiple sources and sets of digitally stored personal data, keeping
both personal and proprietary information safe is a key issue.64
Finally, various stakeholders
(AustriaTech, ASECAP and POLIS consulted through the exploratory interviews) identified
the lack of a trust model for exchanging data between the involved stakeholders as the main
58
representing the European ride-hailing sector
59
representing consumers in the context of standardisation
60
Mentioned by ACEA, Volvo Group and the Norwegian Public Road Authority in their IIA responses
61
GDPR and ePrivacy Directive
62
https://edpb.europa.eu/our-work-tools/our-documents/guidelines/guidelines-012020-processing-personal-
data-context_en
63
https://www.europarl.europa.eu/RegData/etudes/STUD/2018/615635/EPRS_STU(2018)615635_EN.pdf
64
https://publications.jrc.ec.europa.eu/repository/handle/JRC116644
16
hurdle to enable the necessary data flow for the (quality) operation of ITS services. They
highlighted that MaaS deployment requires a fair and non-discriminatory system outlining the
rights and obligation of involved stakeholders, access and data sharing and reuse conditions.
Another factor elaborated in the evaluation of the Directive was that the actual sharing of data
beyond static network information has been very limited.65
This is despite the fact that NAPs
have been set up as a potential backbone for the digital transport infrastructure and an entry
point for sharing data. An approach to develop a coordination mechanism to federate NAPs is
currently in preparation and aims to stimulate and accelerate the coordinated provision of data
(addressing also problem driver B).66
The current lack of data sharing can also be attributed to a lack of awareness of incentives and
benefits to collect and share such data amongst the different stakeholders involved in the data
value chain (e.g. data producers, intermediaries, users etc.). The support study on RTTI defines
essential services and identifies the data types necessary for the operation of these services,
which currently lacks availability. 67
The study concludes that there is a clear added value for
making these data available in a phased manner, initially for a strategic road network and then
expanding to the entire transport network.
Respondents to the targeted survey agreed with the contribution of Problem Driver C in
hindering the deployment and use of ITS services across the EU as can be seen in Figure 5.
Figure 5: Survey responses regarding the relevance of Problem Driver C
There also seems to be a lack of policies and measures aiming to make fare information and
service sharing possible, resulting in a barrier for the uptake of certain ITS services.68
Some of
the stakeholders responding to the IIA suggested that the lack of two-way sharing of data
65
KPI on the availability of dynamic data on NAPs used in Member State reporting
66
https://ec.europa.eu/transport/content/2020-call-for-proposals-nap_en
67
https://op.europa.eu/en/publication-detail/-/publication/043ee22b-643b-11eb-aeb5-01aa75ed71a1
68
https://cordis.europa.eu/project/id/723314/results
17
between transport users, the public and private sectors may be a contributing factor. A number
of stakeholders suggest that there is a minimum level of standardised data that would need to
be shared to overcome this problem. However, differences in opinions persist as to how far the
sharing of data also includes private sector data. A limited number of Member States have
declared their intention to make also dynamic data available through their NAPs.69
2.3. How will the problem evolve?
In the absence of further EU level intervention to address the problem and its drivers, it is likely
that the deployment of a number of ITS services that rely on EU-level standardised data streams
will remain slow and fragmented, hampering innovation. In particular, ITS services will likely
function primarily at a local, regional or national level as is currently the case, with limited
cross-border interoperability and only at a later stage considering integrating EU-level services.
In the absence of additional EU level intervention, the problem drivers contributing to the
problem would likely persist. Specifically, Problem Driver A: Lack of interoperability and
continuity of applications, systems and services (across different Member States and modes of
transport), cannot be fully resolved by actions undertaken at a Member State or regional level
alone. The Member State reports on the implementation of the Directive paint a picture of
incomplete deployment of ITS services and infrastructure and availability of relevant data
along the different road types within Member States, with deployment taking up predominantly
within the TEN-T network. This points to the fact that deployment of continuous ITS services
is unlikely until relevant infrastructure and data are delivered across the whole of the EU
transport network. There is no indication that future Member State priorities will converge to
the point of achieving full deployment of ITS services across the EU in the short- or mid-term.
Beyond these continuity concerns, stakeholders also raised the high risk of fragmentation of
(emerging) ITS services due to the use of different standards by different stakeholders70
.
Service interoperability will thus most probably develop on an ad hoc basis between service
providers of different modes or regions but lacking a universal framework of application. The
majority of respondents to the targeted survey, shared the view that most of the ITS service
types identified, would only be fully available towards 2040 as illustrated by the examples
presented in Figure 6 for “travel information” and “V2V C-ITS” services. As such, only partial
availability of services is expected until then, with travel information services expected to be
deployed earlier than C-ITS services.
Looking at the expected development of Problem Driver B: Lack of concentration and effective
coordination among stakeholders, this also does not seem possible to be tackled in the absence
of further EU-level action. Although stakeholder cooperation is already a fact for some ITS
related topics (e.g. NAP coordination), this is largely a result of EU action. Therefore, in the
absence of further EU-level action, public and private stakeholders could be expected to
continue developing voluntary industry or Member State-led cooperation mechanisms to deal
with specific ITS issues that would not contain the full selection of relevant stakeholders. Such
69
https://ec.europa.eu/transparency/regexpert/index.cfm?do=groupDetail.groupMeetingDoc&docid=43371
70
Indicated in the survey responses of Insurance Europe and Allianz
18
initiatives could be expected to develop a common approach or policies to deploy ITS, but
would do so taking a more narrow geographical or modal view point and in relative isolation
from other groups attempting similar initiatives.
Figure 6: Stakeholders' expectation of the state of deployment of ITS services
Source: Targeted stakeholder survey
Finally, with regard to the Problem Driver C: Limited data availability and access, as well as
lack of common data quality standards and limited exchange and usage of data, no significant
developments are expected without further EU-level intervention. A number of Member States
are currently moving forward in making crucial data for the deployment of ITS services
available (e.g. France has already mandated the availability of MMTIS data for persons with
reduced mobility71
). However, this is not expected to expand to the whole of the EU. As data
sharing and reuse is currently often left at a voluntary basis, the sharing of data will likely
remain limited to the level of individual business agreements. Also, current trust issues
affecting the willingness of stakeholders to share and reuse data can be expected to continue in
the absence of an EU level action, especially on addressing concerns regarding compliance of
ITS deployment with EU data protection legislation.
The deployment of certain innovative services that rely on sharing specific data categories, is
therefore expected to suffer from the lack of incentives to produce, share and reuse specific
high quality, real-time data. Also, such data, where made available, would follow different
quality standards introduced by different Member States or industry stakeholders in the absence
71
Décret n° 2021-836 du 29 juin 2021 relatif à la collecte des données décrivant l'accessibilité des itinéraires
pédestres https://www.legifrance.gouv.fr/jorf/id/JORFTEXT000043714243
19
of an EU-level coordination on this topic intervention taking place. Thus, although it can be
expected that more data will be made available in the future, these would come at different
levels of availability and quality standards across the EU leading to the retention of the problem
of essential data for ITS services being only partially available and used in the future.
3. WHY SHOULD THE EU ACT?
3.1. Legal basis
To ensure the correct functioning of the internal market the Treaty on the Functioning of the
EU (TFEU) establishes the EU’s prerogative to makes provisions for the Common Transport
Policy, Title VI (Articles 90-91) and for the trans-European networks, Title XVI (Articles 170-
171). With this legal framework in mind, EU action allows better coordination for even,
continuous and widespread deployment of ITS, instead of relying on Member States only. This
facilitates travel across the EU for consumers and transport operators. It also helps to avoid
fragmentation of ITS deployment and encourages private service providers to commit to
deployment, knowing the road infrastructure is in place.
3.2. Subsidiarity: Necessity of EU action
While ITS services can be (and are) introduced at regional or national level, the continuity of
the EU transport system requires an EU-wide approach to deal with the problems at stake.
Discrepancies between Member States and local authorities in support measures for the
deployment of ITS could lead to a fragmented market leading to increased costs and reduced
benefits for all stakeholders, including service providers, Member States, local authorities and
transport system users. Different regional approaches may even lead to a complete inability to
deploy specific services involving multi-modal or cross-border cooperation.
Industry-led standardisation through the European Standardisation Organisations contributes
to interoperability, but it is voluntary by nature and allows non-interoperable implementations,
and with many different actors and strong network effects, no actor can introduce an
interoperable solution on its own. Similarly, setting rules at the national level would likely
hinder the provision of continuous ITS services in the Single European Transport Area.
Compatibility between infrastructure and vehicle solutions will need to be assured across the
EU in order to fully benefit from ITS. In addition, to ensure effective synergies with the
deployment of new safety technologies and the roll-out of CCAM across the EU a more
harmonised approach at EU level is needed. Only when reassurance is given that harmonisation
is achieved at EU level, implying also, crucially, that vehicles will benefit from infrastructure
services all across the Union, does deployment make sense. Similarly, though the business case
is calculated differently for the public sector, it makes no sense to invest unless large portions
of the fleet are expected to be equipped in the near future.
EU-level coordinated action is already introduced as an optimal approach for the deployment
of the current version of the ITS Directive and EU action is foreseen to tackle the four priority
areas identified in the Directive. A revision of the ITS Directive would aim to further yield
20
results in these key priority areas as well as in new defined policy areas aiming to cover
emerging ITS service. Stakeholder consultation also revealed support for action at EU level.
3.3. Subsidiarity: Added value of EU action
The main benefits of EU action lie in the continuous ITS services across the EU which the
initiative aims to achieve. Travel throughout the EU should become safer and more efficient,
whereby less advanced Member States will be able to benefit from the experience of more
advanced Member States. This should in turn improve the functioning of the internal market,
through a smoother and more coherent travel experience for passenger and freight transport,
and support the EU's objective of economic, social and territorial cohesion.
A framework for continuous ITS services, supported by a broad group of stakeholders, would
also help create a supportive ecosystem for the research and innovation in new ITS services
and technologies such as MaaS. The development of highly automated road transport is part of
a global race and competition, including stakeholders from outside the traditional automotive
sector. As (cooperative) ITS is a key enabler for automation and deploying CCAM in the EU,
its continuous, harmonized and EU-wide deployment would improve the EU’s international
competitiveness in this field.
4. OBJECTIVES: WHAT IS TO BE ACHIEVED?
4.1. General objectives
This initiative aims to increase the deployment and operational use of ITS services across the
EU, to improve road safety, increase the efficiency of the transport system as a whole and help
linking all transport modes to foster a multimodal transport system and, and in doing so, to
reduce the negative external effects of transport.
This contributes to the two key priorities for the transport system described in the Sustainable
and Smart Mobility Strategy: the decarbonisation and digitalisation of the EU transport sector.
In addition, this will contribute to reducing accidents and achieving Vision Zero.
4.2. Specific objectives
All ITS require the exchange of data. To make that happen the data needs to exist, be
standardised, digitalised and available for sharing. In addition, there needs be trust between the
parties sharing the data and coordination between multiple actors, particularly when effective
delivery of the service depends on parallel investments. Furthermore, the very positive cost
benefit ratio of ITS applies when deployment takes place at the scale of the Union. For
example, it makes much less sense to equip vehicles when the public data needed to deliver the
service is only available in a fragmented manner.
General objective Specific objective Indicator
Increase the
deployment and
SO1:Increase interoperability and
cross-border continuity of
 Increased financial and administrative
capacity to accelerated ITS deployment
21
General objective Specific objective Indicator
operational use of ITS
services across the EU,
to improve road safety,
increase the efficiency
of the transport system
as a whole and help
linking all transport
modes to foster a
multimodal transport
system and, and in
doing so, to reduce the
negative external
effects of transport
applications, systems and services
supporting a common ITS market
 Increased interoperability and continuity
of services across Member States
 Creation of common standards, principles
and quality requirements for emerging
ITS services
 Increased interoperability of data
generated by all modes
SO2: Establish a clear and effective
coordination and concertation
process for all ITS stakeholders
(including stake-holders relevant in
the multimodal context of the
Directive)
 Stronger cooperation in ITS governance,
industry buy-in
 Comparable monitoring of ITS
deployment across MSs
SO3: Ensure improved data
availability, access and quality
standards used and facilitate the
exchange and usage of data
supporting ITS services
 Solutions for (trust) issues with data
protection, privacy and liability
 Increased incentives / awareness to collect
and share ITS data
From this, three specific objectives (matching the three problem drivers defined in chapter 2.2)
were identified.
SO1: Interoperability is a necessary precondition for reaching cross-border continuity of ITS
services. For existing services a lot of work has already happened but for emerging ITS services
like multimodal services and when combining data from different modes, issues remain.
Without this, deployment will by definition be fragmented and likely be delayed. As a result
transport users cannot or will not benefit from such services when travelling in the Union, even
when reaching regions that have invested in deployment. This will limit the potential of such
services and fail to create the necessary scale required to unlock larger investments and support
a European ITS market. Success will thus depend on addressing these issues and be measured
by the financial and administrative capacity to develop innovative multi-modal mobility
services that depend on this data and the deployment of all services.
SO2: ITS services are beneficial for individual transport users, as well as for transport network
managers, road operators, vehicle manufacturers, mobility service providers, fleet managers
etc. ITS services can also be offered by public authorities, road operators and industrial service
providers. Moreover, some ITS services target multimodal travel services and require the
collaboration of stakeholders from other modes. That implies that accelerated and harmonised
deployment of ITS services can only happen when clear and effective coordination and
concertation processes exist for all ITS stakeholders. Success will depend on aligning public
and private interests, matching investments from both sides and the deployment of ITS that
successfully builds on and combines data from public and private sources. In addition,
22
comparable monitoring of ITS deployment helps understanding what already exists and works
well, realising continuity of services and creating incentives to build on that.
SO3: in order to exchange data it first of all needs to be available. Next, the data also needs to
be accessible, in a standardised format, and of high-quality, meaning not only the level of detail
but also making sure that the data is not outdated. When personal data is involved, for example
when C-ITS or in-vehicle data is used, issues on data protection, data ownership, privacy and
liability need to be resolved. Trust amongst stakeholders is important, particularly when
dealing with commercially sensitive data, and to be complemented by suitable business models,
from both public and private perspective. Common solutions for all interested parties are
needed as both vehicles and infrastructure would benefit greatly from increased data
availability and sharing. In fact, for higher levels of automation many now consider this a
necessary enabler. Success would be the timely availability of the necessary high quality data
(such as traffic regulations) to support advanced vehicle features, whilst in-vehicle data is
available for enriching traffic management and other infrastructure services. Success would
also mean sharing of relevant data by all mobility providers to enable multi-modal mobility
services. A by-product/additional manifestation of that success would be the continued
presence of EU technology providers and automotive OEMs amongst the global leaders in the
mobility sector.
5. WHAT ARE THE AVAILABLE POLICY OPTIONS?
5.1. What is the baseline from which options are assessed?
The EU Reference Scenario 2020 (REF2020) represents the starting point for assessing the
options in this IA. The EU Reference scenario 2020 reflects the range of foreseen national
policies and measures of the final National Energy and Climate Plans that Member States
submitted in 2019 according to the Governance Regulation72
. The EU Reference scenario 2020
also takes into account the impacts of the COVID-19 pandemic that had a significant impact
on the transport sector. More detailed information about the preparation process, assumptions
and results are included in the Reference scenario publication73
.
Building on the Reference scenario 2020, the Baseline scenario for this IA has been designed
to include the initiatives of the ‘Fit for 55’ package and other measures of the MIX policy
scenario74
. The MIX scenario follows a balanced approach of carbon pricing instruments and
regulatory-based measures to deliver on the ambition of at least 55% emissions reductions by
72
Regulation (EU) 2018/1999
73
EU Reference Scenario 2020 | Energy (europa.eu)
74
The representation of the CO2 standards for light duty vehicles and the revision of the Renewable Energy
Directive in the MIX scenario is not fully consistent with the proposals adopted on 14 July. These however
are not expected to have any impact on the deployment of ITS services relevant for the Baseline scenario of
this impact assessment. In addition, as the road transport and buildings are subject to a separate Emission
Trading Scheme, the emissions from these sectors are capped. This means that if the contribution of renewable
and low carbon fuels is higher than in the MIX scenario this would result in a somewhat lower ETS price but
without a significant impact on transport activity and emissions.
23
2030 and climate neutrality by 205075
. The Baseline scenario is commonly used by this IA and
the one underpinning the review of the TEN-T Regulation (both planned to be adopted in
autumn), to ensure consistency.
The Baseline scenario assumes no further EU level intervention beyond the current ITS
Directive. It assumes the continuation of the application of the ITS Directive provisions and
the preparation of standards for the already defined priority areas. It also covers:
 National ITS deployment projects (e.g. C-Roads and ITS corridors) are expected to result
in important ITS deployment at regional level, but not widespread adoption.
 Industry announcements and identified trends around ITS deployment.
Without further EU level intervention ITS service usage is projected to progress slowly.
In this IA the existing priority areas and services as described in chapter 1.2 (many of which
are already covered by Delegated Regulations) are complemented by emerging ITS services.
The multi-modal area is strengthened by including booking services and intermodal interfaces
for drivers, whilst traffic management is complemented by mobility management and support
for automated vehicles is also included. The various types of services have been bundled,
taking into account mainly the targeted transport users and the underlying deployment drivers
(see Table 5). The 3 C-ITS bundles (4, 5 and 6) are separate because they rely on
communication between dedicated C-ITS devices (typically installed in vehicles or in the
infrastructure) whilst the information services in the other bundles can generally be delivered
through various non-dedicated means, such as navigation devices and smartphones (e.g.
planning a multimodal trip). This forward-looking extension, and some regrouping, was
subsequently tested in the first open stakeholder workshop. This led to splitting the first bundle,
making a clear distinction between drivers and travellers, again strengthening the multi-modal
angle. The bundles were presented in several workshops afterwards, in which stakeholders
recognised the logic not only in terms of functionality and target users, but also of the required
investments.
75
It should be noted that the MIX scenario underpinning the impact assessments accompanying the ‘Fit for 55’
package covers the initiatives adopted in July 2021 but also some other initiatives of this year and of the
following year (e.g. for transport, CO2 standards for heavy duty vehicles, the revision of the TEN-T
Regulation, the revision of the ITS Directive, the revision of the Rail Freight Corridors Regulation and of the
Combined Transport Directive, etc.). For this reason, only a few adjustments had to be made in order to provide
a suitable Baseline scenario for this impact assessment. This however does not mean that the Baseline scenario
deviates from the balanced approach of the MIX scenario, combining carbon pricing instruments and
regulatory-based measures. These two initiatives were represented in a stylised way in the MIX scenario,
ahead of the respective legislative proposals. In order to provide a meaningful Baseline for the two impact
assessments, showing how the problem would evolve without further EU level intervention, it has been
assumed that only the current EU level legislation (i.e. the current TEN-T Regulation and the current ITS
Directive) is in place for these two initiatives. In addition, for the Rail Freight Corridors Regulation and for
the Combined Transport Directive it has been assumed that only the current EU legislation is in place. This is
because of the important synergies between the revision of the TEN-T Regulation and the forthcoming
revisions of the Rail Freight Corridors Regulation and of the Combined Transport Directive, that need to be
enabled by the availability of high quality infrastructure for their success. All other assumptions were kept
unchanged.
24
Table 5: ITS service bundles
No. Service bundle ITS service type Intended impacts on transport
1a
Information &
booking services
for travellers
 Multimodal travel information service
 Multimodal booking / re-selling
service (including mobility as a
service)
Improved trip planning choices
(time/route/modal)76
leading to:
 Congestion reduction / trip time
 Reduction in fuel consumption /
emissions
 Modal shift
 Reduction of transport costs
(incl. external cost of transport
to society)
 Improvement in resilience and
quality of service
1b
Information and
booking services
for drivers
 Road traffic & navigation service
 Real-time traffic information service
 Parking (and pricing) information
 Re-charging/re-fuelling information
 Intermodal interfaces
2
Travel
management
services
 Traffic incident management systems
 Mobility management services
3
Road safety and
security
applications
 Road safety-related traffic information
 S&S truck parking
 eCall
Improved transport safety
 Reduction of accidents
(fatalities and injuries)
 Reduction of external costs
(caused by accidents)
4
Vehicle-to-
vehicle (V2V)
 C-ITS services such as electronic
brake light & hazardous location
5
Vehicle-to-
Infrastructure
(V2I)
 C-ITS services such as shockwave
damping, in-vehicle speed limits,
green light optimal speed advice and
Signal violation
 Congestion reduction / trip time
 Reduction in fuel consumption /
emissions
6
Future C-ITS
services
 C-ITS cooperative perception services
(day 2) and automation support
services (day 3) – e.g. platooning
 Significant (longer term)
impacts in transport safety and
mobility
Stakeholders contributed to the establishment of the list of ITS services and its bundling during
the targeted interview programme and the series of workshops held (see annex II). Electronic
tolling and payment services were considered at some point but discarded as they are already
regulated outside the scope of the ITS Directive77
. Stakeholder feedback also led to the splitting
of bundles 1a and 1b to clearly identify services having primarily a multi-modal focus targeting
travellers rather than drivers. Some stakeholders questioned whether the bundling reflected any
choices in technology to deliver the services (particularly related to the C-ITS bundles) but that
is not the case. The ITS service bundles do not aim to develop any formal classification but
serve a functional purpose for this IA. Specifically, by grouping together services with
similar/overlapping functionalities, the deployment rates and their impacts can be assessed in
a systematic way, without going into details for the numerous ITS services while at the same
time capturing all the costs and benefits associated to them.
The usage of the ITS services in these seven bundles is what drives impact on the transport
system so the IA estimates the expected increase in ITS service usage in the baseline for all
service bundles until 2040. Services in Bundles 1-3 start from a higher level of usage in 2021
compared to Bundles 4-5 that are reliant on the continued roll out of dedicated infrastructure
76
Provided alternatives to car / truck transport are available.
77
https://eur-lex.europa.eu/legal-content/en/ALL/?uri=CELEX:32019L0520
25
and deployment of equipped vehicles, which take time to penetrate the total fleet. The more
mature ITS services (i.e. travel management services (bundle 1b) and road safety and security
applications (bundle 3)) are projected to reach 70% coverage on TEN-T roads in front runner
countries by 2040, see Figure 7.78
For Bundle 6, which includes services leading to higher
levels of automation, no service usage is projected in the IA. 79
Figure 7: service usage in front runner countries in the baseline
Source: Ricardo et al. (2021), Impact assessment support study
In the Baseline scenario, EU transport activity is projected to grow post-2020, following the
recovery from the COVID pandemic. Road transport would maintain its dominant role within
the EU in 2040, despite the fact that rail transport activity would grow significantly faster.
Congestion costs would increase by about 14% by 2030 and 23% by 2040, relative to 2015.
Congestion on the inter-urban network result from growing freight transport activity along
specific corridors, in particular where these corridors cross urban areas with heavy local traffic.
CO2 emissions from transport including international aviation but excluding international
maritime transport, are projected to be 19% lower by 2030 compared to 2015, and 70% lower
by 2040. The reduction in road transport emissions would be higher, at around 24% by 2030
relative to 2015 (78% decrease by 2040) driven in particular by the proposed CO2 standards
for light duty vehicles, supported by the roll-out of recharging/refuelling infrastructure, but
also by other measures like carbon pricing and energy taxation.
NOx emissions are projected to go down by 56% between 2015 and 2030 (77% by 2040),
mainly driven by the electrification of the road transport. The decline in particulate matter
(PM2.5) would be slightly lower by 2030 at 52% relative to 2015 (79% by 2040).The number
of fatalities is projected to be 22% lower in 2030 relative to 2015 and 28% lower by 2040,
78
Bundle 1a is shown for urban roads and not TEN-T as this is where usage of MaaS and MMTIS services is
expected to be highest. The model also distinguishes between service delivery methods (generic devices such
as smartphones and in-vehicle systems) but the chart does not make this distinction and shows all service
usage. Finally, the model also distinguishes between vehicle types (cars, light trucks, heavy trucks and
busses), in the chart cars are shown as they represent the largest fleet, with the exception again of bundle 1a,
which is associated with travellers and not with drivers or vehicles.
79
Due to their early level of development, there are no concrete studies that have investigated the impacts
considered in this impact assessment, and it is therefore not possible to accurately represent them in the model.
This was confirmed during discussions with stakeholders during the workshops, who agreed that there were
no reliable sources, and stated that the focus of the ITS Directive should be on increasing the deployment of
services with a higher level of maturity, rather than Bundle 6, which is more forward looking.
26
being however far from the milestone of the Sustainable and Smart Mobility Strategy of close
to zero death toll for all modes of transport in the EU by 2050. The number of serious and slight
injuries would go down at lower speed (18% for 2015-2030 and 22% for 2015-2040). More
details on the baseline scenario are provided in Annex 4.
5.2. Description of retained policy measures
As a first step, a comprehensive list of possible policy measures was established after extensive
consultations with stakeholders, expert meetings, independent research and the Commission’s
own analysis. This list was subsequently screened based on the likely effectiveness, efficiency
and proportionality of the proposed measures in relation to the given objectives, as well as their
legal, political and technical feasibility. The retained policy measures are presented in Table 6
and linked to the service bundles (SB) that are expected to most benefit from them. Measures
11, 12, 13, 14 and 15 are implemented, for most in a phased approach, between 2025 and 2030.
All other measures are assumed to be implemented starting in 2025.
Table 6: list of policy measures and service bundles expected to benefit from them
#
Type of
measure
Policy measure Policy measure description Aim of the policy measure
SB
1
Extensi
on of
scope
Adjust the
scope of the
Directive to
explicitly
include MDM
services
The scope of the Directive would be
broadened to explicitly cover ITS
services that support multimodal
mobility.
Improve the deployment of the
relevant ITS infrastructure, continuity
of services, address the lack of
common standards and improve the
interoperability of data generated
across modes.
1a
2
Update
priority
areas
MDM services
The definition of the priority area
would be broadened to ensure that it
clearly covers services in support of
multimodality.
Improve the deployment of the
relevant ITS infrastructure, continuity
of services, address the lack of
common standards and improve the
interoperability of data generated
across modes.
1a
3
Enhanced
traffic/mobility
management
The priority area would be updated by
bringing together ‘mobility services’
and ‘traffic management’ under
‘mobility management’.
Better reflect actions of transport
authorities and prioritise the
deployment of ITS infrastructure that
supports mobility management more
generally.
2
4 CCAM
A new priority area would be
established focusing on CCAM to be
updated to reflect current needs.
Ensure that the subsequent actions
relating to CCAM will be developed
appropriately, accelerating
deployment
4-6
5
Include
(mandatory)
deployment in
scope of
application
The scope of the application of the
priority areas will be expanded from
“standards and specifications” to also
include ‘mandating data and services’.
This will facilitate some of the policy
measures below, which would help to
ensure the deployment of ITS.
All
6 New
standard
s/
specific
ations
New
standardisation
mandate(s)
under Article 8
An extension of the validity of Article
8 will be needed to reflect the new
standardisation requirements.
This will enable the development of
standards for new specifications,
supporting the interoperability
between different modes and for new
services.
All
7
Revision of
specification
for RTTI
Develop specifications for data types
relevant for the delivery of essential
RTTI services, including (1) UVAR;
Common specifications enable the
development of interoperable
datasets, support data exchange with
1b
27
#
Type of
measure
Policy measure Policy measure description Aim of the policy measure
SB
(2) Recharging/Refuelling points and
stations; (3) Historical traffic data; (4)
Other road and traffic specific rules.
The specifications will also define an
extended geographical scope for both
current and new data types.
little transaction effort, foster service
continuity and the faster/cheaper
deployment of more comprehensive
services.
8
Requirements
for the access
to in-vehicle
generated data
for road
operation (asset
and traffic
management)
services
Define, through a separate Delegated
Act, a set of requirements for
providing B2G access to in-vehicle
data. OEMs or service providers that
provide road operation services based
on in-vehicle generated data must:
 List themselves on NAPs,
addressing discoverability of data
 Allow non-discriminatory B2G
access to their services (i.e. same
T&Cs across EU).
A common set of requirements gives
service providers and authorities
knowledge of existing datasets and
improves access to these through
NAPs.
Knowledge of existing datasets as
well as non-discriminatory access
may lead to an improved B2G sharing
and usage of available data and lead
to the deployment of more advanced
services that account for these data.
1b
9
Standards for
in-vehicle
generated data
for road
operation (asset
and traffic
management)
services
Define, through subsequent Delegated
Acts, a standard for in-vehicle
generated data. This will target data
relevant for asset and traffic
management.
OEMs or service providers that
provide (aggregated) in-vehicle
generated data for road operation
purposes must do so following the
defined standards
Common standard allow
interoperability of data for road
operation services, facilitating its
exchange between OEMs, service
providers and road management
authorities, reducing transaction costs
and leading to development of
advanced services related to road and
traffic management.
1b
10
Specifications
for C-ITS (Day
1, Day 1,5 and
Day 2 services)
Define, through a specific Delegated
Act, EU specifications to ensure EU-
wide compatibility, interoperability
and continuity for the deployment and
operational use of C-ITS, including:
 Service definitions and relevant
communication specifications;
 compliance assessment, putting
on the market, and operating ITS;
 Security requirements.
This measure will ensure the
interoperability of relevant C-ITS
services and equipment, fostering
deployment of C-ITS and single
market for ITS components.
Improved security through the use of
a common communication standard is
also expected to improve perception
and trust in C-ITS services,
supporting usage of relevant services.
4-6
11
Mandati
ng data
availabil
ity
Mandate
availability of
crucial RTTI
data
This mandate will oblige local and
national authorities and road operators
to generate (following quality
standards) and make accessible via
the NAPs, in a phased manner, data
on:
 Restricted Vehicle Access Zones
 Traffic regulations and
circulation plans
 Road and lane closures, direction
of travel on reversible lanes,
roadworks and temporary traffic
management measures
Mandating the availability of these
data will lead to improved access,
availability and eventually usage of
data. It will also enable the faster
deployment of RTTI services using
these data.
The measure will implement data
updates on TEN-T first and later
move to full date sets, as well as a
similar, but even later, phased
approach on the entire network
1b
12
Mandate
availability of
MMTIS crucial
data
This mandate will oblige transport
service providers to generate
(following quality standards) and
make accessible via the NAPs data
Mandating the availability of these
data will lead to improved access,
availability and eventually usage of
data. It will also enable the faster
1a
28
#
Type of
measure
Policy measure Policy measure description Aim of the policy measure
SB
types related to the provision of
MMTIS:
 data for PRM users e.g.
accessibility of vehicles and
access nodes (static), status of an
access node feature: operational
lifts / escalators (dynamic)
 Connection points/ access nodes
deployment of travel information
services using these data.
The measure applies to the entire
transport network as of 2028
13
Mandate
availability of
Safe & Secure
truck parking
data
This mandate will oblige transport
service providers to generate
(following quality standards) and
make accessible via the NAPs specific
data related to S&S truck parking
location services for the entire
transport network as of 2028.
Mandating the availability of such
data is expected to lead to improved
access, availability and eventually
usage of data. It will also enable the
faster deployment of S&S truck
parking information services using
these data.
3
14
Mandati
ng
services
Mandate
availability of
(SRTI) services
This mandate will oblige authorities
and organisations responsible for the
operation of the TEN-T
comprehensive road network to
deliver SRTI.
Guaranteed deployment of SRTI
services on TEN-T, possibly leading
to spill-over effects on other parts of
the network.
3
15
Mandate
availability of
Day 1 C-ITS
services
This measure introduces a mandate
for the delivery of C-ITS services in
all new vehicle models after 2028.
The measure will accelerate the
deployment of Day 1 C-ITS services.
4
16
ITS
deploy
ment
principl
es
Update the
principles for
specifications
and
deployment of
ITS
Update Annex II of the Directive,
focusing on transparency of data
availability and equality of access of
the information, data privacy and
transparency of the ranking of
services, in addition to provisions
established in the context of the P2B
Regulation.
Applying a harmonised set of
principles can be expected to increase
trust in the deployed ITS services
regarding their compliance with
critical elements and thus lead to an
improved usage and deployment of
ITS services.
All
17
Governa
nce
framew
ork
Setting-up of
governance and
the facilitation
of national &
EU wide
operational co-
ordination of
NAPs
Develop a governance framework for
the coordination of NAPs in a CEF-
funded PSA, including on monitoring
the availability and accessibility of
data, harmonised levels of service of
the NAPs, harmonised compliance
assessment processes and the
coordinated creation and collection of
data.
A common approach across the
NAPs, including in relation to
creating, collecting and monitoring
data, will improve coordination and
help to support the availability, access
to, and the more efficient and
consistent use of data
All
18
Introduce legal
provisions on
governance of
national & EU
wide
operational
coordination of
NAPs
Ensure the operation of a governance
structure and the continued
monitoring of the availability and
accessibility of data in all Member
States, including harmonised levels of
service of the NAPs, harmonised
compliance assessment processes and
the coordinated creation and
collection of data.
This will ensure a common approach
across all NAPs, including in relation
to creating, collecting and monitoring
data, supporting the more efficient
and consistent use of these data
throughout the EU.
All
19
Governa
nce
framew
ork - C-
ITS
Implement the
European C-
ITS Trust
model
In a new CEF project, continue
implementation of the EU CCMS.
This certificate policy defines
requirements for the management of
public key certificates for C-ITS
The C-ITS trust model is a defining
feature of C-ITS and a necessary
condition to enable trust between all
C-ITS users. It supports the
deployment of C-ITS services.
4-6
29
#
Type of
measure
Policy measure Policy measure description Aim of the policy measure
SB
applications.
20
Introduce legal
provisions on
the EU C-ITS
Trust model
Give the EU CCMS legal status. This
certificate policy defines requirements
for the management of public key
certificates for C-ITS applications.
Providing legal and technical
certainty to the C-ITS trust model will
accelerate the development and
deployment of C-ITS services.
4-6
21
Governa
nce
framew
ork
Further
improve and
streamline the
interaction with
ITS
stakeholders
The way stakeholders will be
consulted in the implementation of the
Directive and in the development of
the delegated acts will be made more
efficient (e.g. by including
stakeholders other than Member
States on implementation objectives)
This will ensure that the relevant
expertise is involved at the most
appropriate points in the process, as
well as ensuring that the concerns of
particularly stakeholders are
sufficiently addressed. In this way, the
measure would help to improve
coordination.
All
22
Improve
reportin
g
Update and
streamline
reporting
obligations
Streamline reporting requirements,
with reporting for all delegated acts
integrated into Member States’
overall reporting on the Directive.
This will reduce administrative
burden, particularly for Member
States.
All
23
Mandate
reporting based
on common
format & KPIs
A mandatory common format for the
MS reports, requiring a minimum
level and quality of data, for the
assessment of progress with the
implementation of the Directive and
its Delegated Acts, supported by
methodological guidance to ensure
that KPIs are measured consistently.
This will make comparisons between
Member States easier and paint a
clearer picture of the state of play
across the EU (e.g. on the
performance of NAPs and on the level
of deployment and use of ITS
services). This could help to facilitate
better coordination between Member
States.
All
24
Enhance
coheren
ce
Improve the
coherence of
the ITS
Directive with
the existing
legal
framework
The approach taken in relation to ITS
services will be aligned with:
 GDPR
 ePrivacy legislation
 Passenger rights legislation
Capitalising upon synergies and
addressing overlaps and conflicts,
increased availability of more
consistent data, improved confidence
in the use of data, helping the
deployment of services and reducing
the administrative burden of data
providers.
All
25
Improve the
coherence of
the ITS
Directive with
expected
initiatives
The ITS Directive will be aligned
with initiatives expected to be in place
as of September 2021:
 The Mobility Data Space
 Upcoming EU framework for in-
vehicle data architecture.
 TEN-T and Rail Freight
Corridors Regulation
Capitalising upon synergies and
addressing overlaps and conflicts,
including mobility data and access to
in-vehicle data. More consistent data
are expected to help with the
deployment and use of services,
reduce the cost related to identifying,
sharing, accessing and using the data
needed to deploy ITS services.
All
Stakeholders were involved in all steps of the process, from the definition of the problem, to
the identification of the policy measures. As such, there is general agreement on the scope of
action needed and the options proposed. The detailed figures below show, for each specific
objective defined in chapter 4.2 a combination of interview and survey responses presenting
stakeholder general agreement with the measures put forward (please note that some measures
address multiple specific objectives, for more details on the links between policy measures and
specific objectives see chapter 5.2.2).
30
Figure 8: stakeholder support for measures addressing SO1
Figure 9: stakeholder support for measures addressing SO2
31
Figure 10: stakeholder support for measures addressing SO3
5.2.1. Measures discarded at an early stage
The collection of real consumption data of vehicles was briefly considered but discarded as
possible updated legislation on this topic is currently being investigated in an IA by DG
CLIMA. Requirements on data types regarding availability of relevant recharging and
refuelling-related data were also considered but are now part of AFIR.80
Regarding access to in-vehicle generated data, in the scope of this initiative, the purpose is to
facilitate the reuse of in-vehicle generated data relevant for road maintenance and traffic
management, not at the level of the vehicle itself, but at the level of aggregation and
interpretation of data for that aim. There are existing standards for the re-use of in-vehicle
generated data under development, but not all stakeholders have yet subscribed to use them.
The adoption of a single standard / single specifications would represent a strong improvement.
A complementary mandate on the sharing of in-vehicle data was briefly considered and well
supported by stakeholders (see Figure 11)81
. Nevertheless, this is an emerging service at this
stage and a mandate was not considered feasible until it is clearer which data is precisely useful
80
As emphasized in recitals 45 and 46 of the proposal for a Regulation of the European Parliament and of the
Council on the deployment of alternative fuels infrastructure, and repealing Directive 2014/94/EU of the
European Parliament and of the Council (COM(2021) 559 final), it is necessary to provide consumers with
sufficient information regarding the geographic location, characteristics and services offered at the publicly
accessible recharging and refuelling points of alternative fuels. Requirements on data types regarding
availability of relevant recharging and refuelling-related data should be laid down in that framework, rather than
under the ITS Directive, following the outcomes of ongoing the Programme Support Action on “Data collection
related to recharging/refuelling points for alternative fuels and the unique identification codes related to e-
mobility actors” (‘IDACS’). The accessibility requirements, meaning the data is accessible on NAP in a
standardised format (i.e. Datex II), are laid down in the ITS Directive framework in Delegated Regulation
2015/962 and cross-referenced with the regulation on alternative fuels infrastructure.
81
The transport industry is somewhat divided on this but this seems mainly related to an ongoing debate on the
possibility for independent service providers to get fair and non-discriminatory access to in-vehicle data and
resources. However, this is the subject of a specific initiative under the type-approval framework (lead DG
GROW) with a new proposal expected by Q2 2022.
32
for such business-to-government services, and how it can best be collected and shared with
infrastructure and road managers.
Figure 11: stakeholder support for a mandate on in-vehicle data (interview and survey responses)
Overall, very few measures were discarded because either stakeholders clearly agreed with the
proposed measure or the measure builds on an existing or already planned initiative (see also
chapter 5.2). Looking into some more detail by type of measure (as used in Table 6):
 Measures on scoping: stakeholder views during the first workshop confirmed the
continued relevance of existing priority areas as well as the update of the scoping of the
Directive with new priority areas. Subsequent stakeholder consultations agreed and
hence none of the proposed measures was discarded.
 Measures on specifications, standards and mandates: these are essentially on/off
options (e.g. you develop a standard or not). For the mandates, proportionality is
particularly important however and only the most crucial data types were included.
Identification of crucial datatypes started with the preparation for the revision of the
Delegated Regulation on real-time traffic information, where alternatives were already
tested and discarded. These were subsequently confirmed during the various workshops
organised in the scope of this IA. The other mandates cover significantly smaller
datasets (e.g. the 8 events considered in the safety related traffic information service).
Regarding services, the mandates are relatively limited, with the deployment of the
safety-related information service on the TEN-T network, and for C-ITS the final
selection of services is open and conditional to a dedicated impact assessment.
 Measures on stakeholder cooperation and governance: these are either high-level or
build on pre-existing actions e.g. NAP cooperation, mandating the KPIs reporting, C-
ITS governance etc. They are widely supported in the stakeholder community and
considered essential for continuation.
 Measures on coherence: Measures were developed specifically to tackle the issues
identified in the legal coherence analysis.
33
5.2.2. Retained policy measures and policy options overview
In Table 7 the policy measures from Table 6 are linked to the specific objectives described in
chapter 4.2. The strong interventions (shown as  below) related to the mandatory
collection of crucial data (PO2) and mandatory provision of essential services (PO3) contribute
to both SO1 and SO3. The retained policy measures were also combined into three policy
options (PO), each building on the previous, i.e. PO2 includes all measures of PO1 and PO3
includes all measures from PO2 (the policy measures are re-ordered to illustrate this).
Table 7: Policy measures, their contributions to the specific objectives and inclusion in policy options
No Policy measure SO1 SO2 SO3 PO1 PO2 PO3
1 Adjust the scope of the Directive to explicitly include MDM services      
PO1
2 Update the priority areas – MDM services      
3 Update the priority areas - enhanced traffic/mobility management      
4 Update the priority areas - CCAM      
6 New standardisation mandate(s) under Article 8      
7 Revision of specification for RTTI      
8 Requirements for the access to in-vehicle generated data for road
operation (asset and traffic management) services
     
10 Specifications for C-ITS (Day 1, Day 1,5 and Day 2 services)      
16 Update the principles for specifications and deployment of ITS      
17 Setting-up of governance and the facilitation of national & EU wide
operational co-ordination of NAPs
     
19 Implement the European C-ITS Trust model      
20 Introduce legal provisions on the European C-ITS Trust model      
21 Further improve and streamline the interaction with ITS stakeholders      
22 Reporting: update and streamline reporting obligations      
23 Reporting: mandate reporting based on common format & KPIs      
24 Various measures to improve the coherence of the ITS Directive with
the existing legal framework (i.e. GDPR, ePrivacy, passenger rights)
     
25 Various measures to improve the coherence of the ITS Directive with
expected initiatives (i.e. Mobility Data Space, in-vehicle data
architecture, TEN-T and Rail Freight Corridors Regulation)
     
5 Expand the scope of application of the priority areas from “standards
and specifications” to include deployment (mandating data & services)
     
PO2
11 Mandate availability of RTTI crucial data      
12 Mandate availability of MMTIS crucial data      
13 Mandate availability of S&S truck parking data      
18 Introduce legal provisions on relation to governance and the facilitation
of national & EU wide operational co-ordination of NAPs
     
9 Standards for in-vehicle generated data for road operation (asset and
traffic management) services

    
PO3
14 Mandate availability of SRTI services      
15 Mandate availability of Day 1 C-ITS services      
As a result, despite all policy options addressing all specific objectives, the majority of
measures addressing SO2 are already included in PO1 and the higher level of ambition from
PO2 and PO3 comes primarily from a stronger intervention to tackle SO1 and SO3.
34
Table 8: Overview of policy options in terms of ambition and level of intervention
No Policy option description Degree of ambition Level of intervention
PO1 Strengthened coordination and deployment principles + +
PO2 Mandate collection and availability of crucial data +++ +++
PO3 Mandate provision of essential services ++++ ++++
5.3. Description of the policy options
As illustrated in Table 7 policy options are built incrementally, with the majority of measures
already included in the first policy option. This is because the critical policy choices revolve
around the scope and level of ambition of the mandates, as these are the most intervening
measures and represent significant investments. The policy options need to provide a good
understanding of how these mandates help reaching the overall goal of deploying ITS, as their
usage is ultimately responsible for the generation of impacts. To bring this out in the clearest
manner possible one policy option introduces the data mandates whilst another introduces the
service mandates. A policy option including service mandates but without the data mandates
was not considered as all services rely on data. Indeed, though the overall objective is to
accelerate the deployment of ITS services, the Directive is an enabling framework and many
actions take place at an upstream level, such as working on the standardisation and availability
of data.
5.3.1. PO1: Strengthened coordination and deployment principles
This first policy option introduces the largest amount of policy measures but nevertheless
mostly takes a light touch approach, including those related to amendments to the Directive to
allow for the expansion of its operation in emerging ITS service areas, addressing shortcomings
in stakeholder cooperation with measures improving coordination and finally, ensuring
coherence of Directive provisions with those of other existing legal instruments. It also includes
measures that aim to institutionalise parts of the governance framework, and aims to future-
proof the Directive to function in the advent of known upcoming EU policy initiatives. Policy
option 1 includes the following measures addressing each of the problem drivers:
 Problem Driver A (measures number 1, 2, 3, 4, 6, 7, 8 and 10): improvements and updates
to the functioning of the ITS Directive to enable it to account for new developments in the
mobility eco-system and the evolving policy priorities in the field of transport as well as to
cover emerging ITS services and to ensure coherence with existing EU legislation. These
include the renewal of the standardisation mandate to allow the development of standards
covering an updated set of priority areas such as standards for in-vehicle generated data for
road operation, the revision of the RTTI specifications and new specifications for mature
and upcoming C-ITS services. These new priority areas include the areas of MDM services,
enhanced traffic/mobility management and CCAM services.
 Problem driver B (measures number 17, 21, 22 and 23): improve stakeholder coordination
through the continuation of NAP coordination in a non-binding legal format and set up a
more formal format for stakeholder involvement in the implementation of the Directive and
35
the preparation of Delegated Acts. Streamline requirements for Member State reporting on
the implementation of the Directive and Delegated Acts (currently each Delegated Act
introduces separate reporting requirements) including the use of a set of common KPIs.
 Problem driver C (measures number 16, 19, 20, 24 and 25): facilitate data sharing and
reuse between stakeholders by introducing a set of common principles for the deployment
of ITS services (e.g. on accessibility of the information, data privacy and transparency of
the ranking of services) as well as for the non-discriminatory sharing of in-vehicle data for
purposes of asset and traffic management. The application of the C-ITS Trust model82
becomes embedded in legislation to increase trust in C-ITS services. Finally, in addition to
ensuring coherence with existing legislation (e.g. GDPR and ePrivacy), this Policy Option
aims to further future-proof the ITS Directive ensuring coherence with known upcoming
EU initiatives such as the ones related to the revision of the TEN-T and Rail Freight
Corridors Regulations, in-vehicle architecture and the European Mobility Data Space.
5.3.2. PO2: Mandate collection and availability of crucial data
This strong intervention makes the collection and sharing of data crucial for the operation of
essential services mandatory as a means to boost the deployment of such services. These
measures aim predominantly to improve data availability, quality, access exchange and usage
while all other aspects of Policy Option 1 are retained. More specifically, it will include the
following measures for each problem driver:
 Problem drivers A and C (measures number 5, 11, 12 and 13): this policy option will
expand the scope of application of the priority areas from “standards and specifications”
and introduce the possibility to develop mandates for collecting and making available all
data considered crucial for the deployment of essential services in the priority areas of
RTTI, MMTIS and S&S truck parking. In doing so, this policy option also enables the
development of data quality standards applicable for the mandatory sharing of the crucial
data types required for the delivery of these essential services. In that respect, specific
Delegated Acts for each priority action are to be included to develop the definition of
essential services, the definition of crucial data needed to deliver these services, the
definition of the geographical scope and time-horizon for the data mandate as well as the
development of the required data quality standards.
 Problem driver Β (measure number 18): support the data sharing mandate by embedding
the NAP coordination platform in legislation.
82
C-ITS connects all road users with each other and with infrastructure elements. Exchanging messages requires
trust (think for example about safety messages that trigger automated reactions from vehicles). This trust
comes from digitally signing all messages, but for that to be possible all C-ITS stakeholders need to be part
of the same trust model, i.e. agree to a common set of security requirements. Other than ensuring
(cyber)security the trust models also helps addressing data protection issues by pseudo-anonymising all
messages
36
5.3.3. PO3: Mandate provision of essential services
This strong intervention foresees the possibility to introduce mandates for the deployment of
essential services through Delegated Acts. It especially capitalises on the increased data
availability, quality, exchange and usage promoted by Policy Option 2 (Driver C) and aims to
further support the deployment of interoperable and continuous services (Driver A). More
specifically, in addition to the measures under PO2 and PO1 it includes:
 Problem driver A (measure number 9): Development of a mandatory standard for in-
vehicle generated data facilitating their sharing and integration in ITS services.
 Problem driver A and C (measure numbers 14 and 15): Expansion of the scope of
application of the priority areas and mandating the availability of data required for essential
services and for the deployment of such services. Specific Delegated Acts for each priority
area will develop the definition of essential services, the appropriate quality standards, as
well as the definition of the geographical scope and time-horizon for mandatory
deployment of those services. This mandate focuses on road safety services and will cover
the areas of SRTI and Day 1 C-ITS deployment. To support this deployment mandatory
equipment of new vehicles with dedicated C-ITS stations from 2028 onwards is included.
 Problem driver B: no additional measures
6. WHAT ARE THE IMPACTS OF THE POLICY OPTIONS?
This section summarizes the main expected economic, social and environmental impacts of
each policy option. In terms of time horizon, the assessment has been undertaken for the 2021-
2040 period. The measures that are part of the POs will not all be implemented at the same
time, notably, the data availability mandates in PO2 (measures 11, 12 and 13) and the service
availability mandates in PO3 (measures 14 and 15) are modelled from 2028 and 2030 onwards.
All other measures are assumed to be implemented starting in 2025. The analysis presented in
this section covers the EU27 scope. Costs and benefits are expressed as present value using a
4% discount rate. The assumptions on the take-up rate of the specific services - as well as their
impacts - feeding the ASTRA-TRUST model are based on the best, and most relevant, data
identified in literature. Stakeholders were consulted in several workshops on these
assumptions, including primary cost and impact estimates for all service bundles. The usual
assumptions in monetising externalities are also relevant, for example we cannot model every
individual trip but use units representing averages of all types of trips. Additionally,
assumptions were introduced to extrapolate and cover possible data gaps in different Member
States and road-types, as well as to address potential overlapping effects of services. As a result,
we obtain a reliable estimate of the scale of magnitude of the expected impacts. More details
on modelling are provided in Annex 4 "Analytical methods".
37
6.1. Economic impacts
Deployment, investment and operating costs
The deployment of ITS infrastructure over the 2021-2040 period is presented in Table 9 for the
baseline and policy options. The deployment assumptions, linked to the policy measures
included in each option, build on significant expert input and stakeholder consultation.
Table 9: Cumulative deployment over the 2021-2040 period supporting ITS services
Deployment of ITS Baseline PO 1 PO 2 PO 3
New vehicles equipped 106,289,623 145,054,914 145,054,914 199,744,597
Smartphone used for in-vehicle ITS services 90,443,469 111,093,635 196,424,764 193,092,502
Total ITS users 196,733,092 256,148,549 341,479,678 392,837,099
New infrastructure (RSU) 20,250 45,599 45,599 155,552
New infrastructure (RSI) 22,117 32,940 186,247 196,344
New infrastructure (TMC) 115 159 402 425
Source: Ricardo et al. (2021)
To deploy ITS services costs are incurred by both the public and private sector, notably by the
road authorities and ITS service providers, including vehicle manufacturers. An overview per
policy option for various types of costs is presented in Table 10. Roadside units are required to
support C-ITS services, and costs are highest in PO3 as the mandatory equipment of vehicles
is expected to trigger significant voluntary investments on the infrastructure side. New and
upgraded roadside infrastructure supports data collection and information sharing across all
ITS services. While most NAPs have been set up, they are in various stages of operation and
ongoing costs will scale according to the number and quantity of data sets that are supported.83
Central ITS subsystems include traffic management centres and systems that support overall
administration and management of road systems. The mandatory data collection proposed in
PO2 is responsible for the cost increase in these categories. Mobile systems connect the users
to the infrastructure and costs are dominated by in-vehicle systems, which are required for the
delivery of C-ITS services whilst smartphone costs only include application development as
ownership and data costs are assumed to be covered and will not be affected by the policy
options. While costs in PO1 and PO2 have a similar increase, related to policy measures that
align GDPR, ePrivacy and passenger rights and the C-ITS trust model provisions, all increasing
trust in the system, the costs increase significantly in PO3 as this includes mandatory
equipment of new vehicle types from 2028 onwards.
Table 10: Cost for each PO compared to the baseline (EUR bn), expressed as present value over 2021-2040
Sector Cost component Baseline PO1 PO2 PO3
Total Net Total Net Total Net
Public
Roadside units 0.2 0.4 0.2 0.4 0.2 1.3 1.1
Roadside infrastructure 6.0 6.9 0.9 9.2 3.2 9.3 3.3
National access points 0.7 0.8 0.1 1.1 0.4 1.1 0.4
Central ITS sub-systems 1.0 1.1 0.1 1.6 0.6 1.6 0.6
83
https://op.europa.eu/en/publication-detail/-/publication/043ee22b-643b-11eb-aeb5-01aa75ed71a1
38
Sector Cost component Baseline PO1 PO2 PO3
Total Net Total Net Total Net
Total infrastructure 7.8 9.2 1.3 12.3 4.4 13.2 5.3
Private
In-vehicle systems 16.3 22.5 6.2 22.5 6.2 31.8 15.4
Smartphone and applications 0.0 0.01 0.01 0.02 0.02 0.02 0.02
Total mobile equipment 16.4 22.5 6.2 22.5 6.2 31.8 15.4
Source: Ricardo et al. (2021), impact assessment support study
These costs are of course expected to boost service usage, which is presented for all service
bundles across all policy options in Figure 7, Figure 12 and Figure 13. PO1 is expected to result
in smaller improvements, whilst step-change improvements are expected from PO2 and PO3.
For information services (B1a and B1b) the mandatory provision of data in PO2 is the main
driver for accelerated usage (these services are not covered by PO3 and do not require dedicated
in-vehicle equipment, in the chart lines of PO2 and PO3 overlap). The same is true for travel
management services (B2), the only bundle not targeted by dedicated measures at this stage.
Road safety service usage (B3) is expected to increase markedly thanks to mandates from both
PO2 and PO3, whilst C-ITS services (B4 and B5) benefit from the mandatory equipment of
vehicles in PO3 (PO2 does not cover C-ITS, in the chart lines of PO1 and PO2 overlap).
Figure 12: Service usage of information and booking bundles in front runner countries across policy options
Figure 13: Service usage of travel management and road safety bundles in front runner countries across policy
options
39
Figure 14: Service usage of C-ITS bundles in front runner countries across policy options
Administrative costs
The costs to public authorities from the requirements to review and update the national policy
frameworks (NPFs) and report on the implementation are similar as in the baseline. Monitoring
costs may increase to some extent to report on compliance with the mandatory provision of
crucial data and essential services. Stakeholders highlighted that hundreds of authorities across
Europe would be involved, which is challenging for smaller municipalities as they might lack
the know-how and resources, leading to increased coordination costs. The RTTI support study
estimates the administrative burden resulting from a data collection mandate covered under
PO2 and PO3 in this IA at just over €18 million (present value) for the period 2021-2030.84
The estimated cost includes personnel cost for data collection, processing and maintenance,
coordination, standardisation and training, but focusses on the actual collection of data, going
beyond the administrative costs resulting from it, which can reasonably be assumed to be lower.
On the other hand, the provision of standardised data formats, a common reporting format and
KPIs, and alignment of reporting requirements (from Delegated Regulations and Directive)
will simplify overall reporting under the Directive and reduce administrative costs. The
digitisation of processes leading to the creation of digital information should also reduce the
burden of transmission of information to third parties (e.g. transmission of traffic regulations
updates to service providers, which would be done only once through the National Access
Points). Whether the expected increases and decreases compensate or whether one is higher
than the other is however very difficult to quantify. Sources that have been used to try to
estimate these costs include interviews carried out as part of the IA, the RTTI support study,
the 2020 ITS Member State reports, and feedback from some cities and road authorities. None
of the reported costs were, however, sufficiently granular for this purpose, nor could they be
compared.
84
https://op.europa.eu/en/publication-detail/-/publication/043ee22b-643b-11eb-aeb5-01aa75ed71a1 the timeline
is not the same as the period considered in this IA but the period would cover all the initial investments to
create the data and its supporting infrastructure. Maintenance and operational costs, including coordination
costs, for the period 2031-2040 are expected to be significantly lower
40
Urban travel time costs
Several ITS services target reductions of (urban) travel time, for example through increased
ease of use of multimodal solutions or RTTI. These services types are strongly stimulated by
the data mandates in PO2, leading to very large time savings.
Table 11: Monetised urban travel time saving for EU27 (EUR bn), expressed as present value over 2021-2040
PV 2021-2040 relative to baseline
Cost category Baseline PO1 PO2 PO3
Travel time 6,164.0 -43.0 -138.8 -144.5
Source: ASTRA / TRUST model
The mandatory equipment of vehicles in PO3 enables services such as green light optimal
speed assistance, which bring additional time savings. These present reductions in overall
annual urban travel time (0.7%, 2.3% and 2.3% in 2040 compared to the baseline for PO1, PO2
and PO3 respectively). Given the high number of hours lost in traffic, the monetary value of
these savings is significant.85
Fuel consumption costs
A range of ITS services have a positive impact on fuel consumption. RRTI will help to improve
journey efficiency by influencing vehicles to take optimal routes from a time or even fuel
efficiency perspective, which drives the reduction in PO2. The effect of mandatory equipment
of new vehicles with C-ITS stations in 2028, enabling services that support smoother traffic
flows, becomes noticeable after 2030 and drives the even larger savings in 2040 of PO3.
Table 12: Fuel consumption (in million toe) in 2030 and 2040 for the baseline and policy options
These represent significant reductions in overall fuel consumption as can be seen in Table 13.
Table 13: Monetized fuel costs saving for EU27 (EUR bn), expressed as present value over 2021-2040
PV relative to baseline
Cost category Baseline PO1 PO2 PO3
Fuel consumption 790.0 -0.6 -2.1 -2.4
Source: ASTRA / TRUST model
85
The monetary value was calculated based on the cost of time values from the 2019 Handbook of External
Costs of Transport
Year Mode Baseline PO1 PO2 PO3
2030
Annual fuel consumption in 2030 202 201.8 201.1 201
Saving relative to the baseline in 2030 - 0.19 0.85 0.92
% savings relative to the baseline - -0.10% -0.42% -0.46%
2040
Annual fuel consumption in 2040 123.6 123.4 123.2 122.8
Saving relative to the baseline in 2040 - 0.2 0.42 0.77
% savings relative to the baseline -0.16% -0.34% -0.62%
41
Impacts on transport activity and modal shift
The model shows no discernible impact on total passenger transport activity but Table 14 does
show a (very) small increase of freight transport activity (which is more price-sensitive). Road
transport benefits most from the deployment of ITS services and more efficient road transport
leads to a modal shift towards road. MaaS and mobility management services are an exception
and these are not yet included in this analysis as desk research identified very little evidence
on the impact of these services. To account for this, two additional sensitivity model runs were
performed (see chapter 7.5) to evaluate the potential of MaaS and mobility management
services to compensate for the small modal shift observed in Table 15 for the more ambitious
Policy Options.
Table 14: Freight transport activity (total of all modes) for EU27
Year Freight transport (billion tkm/year) Baseline PO1 PO2 PO3
2030
Transport activity 2,898 2,898 2,899 2,899
% difference - 0.00% 0.03% 0.03%
2040
Transport activity 3,149 3,149 3,152 3,152
% difference - 0.02% 0.09% 0.09%
Source: ASTRA / TRUST model
Table 15: Modal split for passengers
Source: ASTRA / TRUST model
Impact on GDP
The ASTRA model also makes an assessment of the impact of each policy option on GDP.
These are mainly driven by investments in support of ITS. The 2030 and 2040 annual impacts
relative to the baseline are shown in Table 16, which shows modest impacts in PO1 and
marginally higher impacts in PO2 (driven by infrastructure investments needed for mandatory
data collection) and PO3 (driven by vehicle investments in mandatory C-ITS equipment), with
a maximum of increase of 0.12% relative to the baseline in 2040 for PO3.
Table 16: Impacts on GDP for EU27
Year PO1 PO2 PO3
2030
Increase (EUR bn) 1.5 8.6 8.9
% difference to the baseline 0.01% 0.07% 0.07%
2040
Increase (EUR bn) 4.3 16.2 17.3
% difference to the baseline 0.03% 0.11% 0.12%
Source: ASTRA / TRUST model
Year Mode Baseline PO1 PO2 PO3
2030 Car 80.2% 0.1% 0.3% 0.3%
Bus 9.4% 0.0% -0.2% -0.2%
Train 10.5% 0.0% -0.1% -0.1%
2040 Car 79.9% 0.1% 0.4% 0.3%
Bus 9.0% 0.0% -0.2% -0.1%
Train 11.1% -0.1% -0.2% -0.2%
42
Impact on internal market and competition
All policy options are expected to improve the functioning of the internal market, albeit at
different levels. In particular, new specifications foreseen to be developed under PO1 will
support the development of a common EU market for ITS services. These measures will
especially prevent the fragmentation of the market that would take place should different data
standards be developed at a national, local or operator level, which is already an issue today
for e.g. UVAR regulations. It will also create a level playing field, as it guarantees that all
companies will have equal access to the data shared by public authorities, whilst provisions for
the implementation of the C-ITS Trust model will strengthen the internal market for C-ITS
equipment. The mandate to collect and share data for MMTIS, RTTI and S&S truck parking
in PO2 can be expected to further strengthen the internal market. Guaranteeing the availability
of crucial data of uniform quality fosters the development of EU-wide ITS services for the
transport sector and a level playing field for transport operators. The essential service mandate
in PO3 further supports the development of the EU level playing field.
Impact on Innovation
Impacts on innovation can be expected to be delivered through two mechanisms, first, common
data specifications and ITS standards preventing market fragmentation and allowing for the
accumulation of a critical mass for the development of innovation. All policy options deliver
on this however the introduction of mandatory standards for in-vehicle generated data in PO3
is expected to be a game changer, as it would allow the development of innovative services
integrating data from sources currently unavailable. Second, improved data availability and
quality allowing for the development of innovative ITS services making use of the increased
data provision. This is predominantly related to the data mandates in PO2. The mandatory
introduction of C-ITS systems in new vehicles post 2028 will assist in reaching a critical market
mass, promoting the development of innovative services for these systems.
Impact on SMEs
SMEs are not a specific target of the policy measures and there is no indication that a
differentiated impact can be expected to companies of different sizes. However, a fragmented
market, as would have been the case without the introduction of new data specifications and
standard requirements and the widespread use of NAPs, may produce a comparative advantage
for larger companies compared to SMEs. In a harmonised market, as far as standards are
concerned, SMEs will benefit from lower entry barrier to expand their operations and compete
on an equal basis with larger enterprises. In that respect, the measures included in PO1 are
expected to generate the most impact on SMEs, with no additional impacts from PO2 and PO3.
6.2. Social impacts
Impact on road safety
Several of the ITS services considered in this IA specifically aim to improve road safety and
to decrease both the number and severity of accidents. The numbers presented here do not
include the improvement in road safety, resulting from a modal shift from passenger car travel
43
to safer modes such as bus and train, related to the deployment of MaaS and mobility
management services, which as discussed in chapter 6.1 are difficult to quantify at this moment.
All policy options show a reduction in the number of accidents relative to the baseline for both
2030 and 2040, albeit a moderate difference in 2030 (see Table 17) as the uptake of C-ITS
equipment is still low then. All accident types (fatalities, serious injuries and minor injuries)
are projected to decrease under each of the policy options. Minor injuries are most common
and are thus predicted to see the greatest reductions in absolute terms compared to the baseline
in all policy options.
Table 17: Annual accidents and accidents avoided relative to the baseline
2030 2040
Annual
accidents
Relative to
the baseline
% reduction
relative to
the baseline
Annual
accidents
Relative to
the baseline
% reduction
relative to
the baseline
Baseline
Fatalities 18,347 - - 16,655 - -
Serious injuries 247,699 - - 224,654 - -
Minor injuries 863,934 - - 799,892 - -
PO1
Fatalities 18,315 32 0.2% 16,496 159 1.0%
Serious injuries 247,291 407 0.2% 222,475 2,179 1.0%
Minor injuries 862,752 1,182 0.1% 792,729 7,163 0.9%
PO2
Fatalities 18,244 104 0.6% 16,400 255 1.5%
Serious injuries 246,709 990 0.4% 221,611 3,043 1.4%
Minor injuries 861,624 2,310 0.3% 791,002 8,890 1.1%
PO3
Fatalities 18,195 152 0.8% 15,898 757 4.5%
Serious injuries 246,069 1,629 0.7% 214,735 9,919 4.4%
Minor injuries 859,477 4,457 0.5% 767,363 32,529 4.1%
Source: Ricardo et al. (2021)
However, the reduction in fatalities is where the greatest relative benefits are realised, reaching
a maximum 4.5% reduction in 2040 in the case of PO3, which is three times that of PO2 in the
same year (1.5%). PO3 is also expected to have the greatest reduction in total accidents (43,206
in 2040) by considerable margin, which can be explained by the marked increase in road safety
services deployment and uptake due to the introduction of a mandate covering SRTI and C-
ITS services. The relatively low impact in 2030 is because the mandatory equipment, for new
vehicles only, is from 2028 onwards. Looking at the external costs of accidents, expressed as
present value over the 2021-2040 period, as shown in Table 18, PO3 shows the largest savings
relative to the baseline.
Table 18: External costs of accidents expressed as present value over (2021-2040) for EU27 (EUR bn)
PO1 PO2 PO3
Difference
to baseline
% difference
to baseline
Difference
to baseline
% difference
to baseline
Difference
to baseline
% difference
to baseline
Fatalities 1.8 0.25% 4.0 0.55% 8.5 1.16%
44
PO1 PO2 PO3
Difference
to baseline
% difference
to baseline
Difference
to baseline
% difference
to baseline
Difference
to baseline
% difference
to baseline
Serious injuries 3.9 0.25% 7.0 0.44% 17.0 1.06%
Minor injuries 1.0 0.22% 1.4 0.32% 4.1 0.93%
Total 6.7 0.24% 12.3 0.45% 29.5 1.07%
Source: Ricardo et al. (2021)
Affordability of transport services
Table 19 presents the impacts of each policy option on average transport expenditures per
person. These transport expenses are reported by the ASTRA-TRUST model and include
transport costs for road bus and rail86
. Each policy option results in average savings per person
due to the increased deployment of ITS services that reduce transport costs. PO1 generates a
0.3% saving in 2040 relative to the baseline as a result of the somewhat increased ITS service
deployment it brings. This saving increases to up to 0.8% for PO2 and PO3 which through the
mandates for data and services lead to a considerably increased usage of services that have an
impact on reducing transport expenditure (through the reduction of fuel costs).
Table 19: Average expenditure for mobility per person (Euro/person-year)
Year Baseline PO1 PO2 PO3
2030
Annual transport expenditure per person € 801 € 800 € 796 € 796
% difference to the baseline - 0.2% 0.7% 0.7%
2040
Annual transport expenditure per person € 715 € 713 € 709 € 709
% difference to the baseline - 0.3% 0.9% 0.9%
Source: ASTRA / TRUST model
Impact on health
Impacts on health are expected to occur primarily as a result of changes in air pollution
achieved by the various Policy Options. These impacts are quantified and monetised in chapter
6.3. Further positive impacts on health can be expected from the increased use of active modes
in the context of multimodality as promoted by the deployment of MaaS and mobility
management services. Such effects would be present in all policy options but can be expected
to be higher in PO2 (and PO3) where their deployment is supported by a MMTIS data mandate.
Impact on persons with reduced mobility
MMTIS for people with disabilities and reduced mobility is seen by the relevant representative
organisation - European Disability Forum - as being at risk of continued market fragmentation.
In that respect, under PO1, the continued deployment of common data standards could help
mitigate this risk for new services. However, the introduction of the mandatory sharing of
MMTIS data under PO2 and PO3 can be expected to produce the largest effect on people with
disabilities or reduced mobility. The mandatory availability of accessibility-related data for the
functioning of essential services under these POs, supports the potential development of
86
Thus, the difference with the figures reported in the EU Statistical Pocketbook for transport that includes also
aviation, IWT and maritime transport as well as costs of courier services and warehousing activities.
45
relevant multi-modal travel information services for this passenger group that can contain real-
time updates of accessibility-critical information.
Impact on employment
The increase in deployment of ITS services under the different policy options can be expected
to lead to second order employment effects as a result of the increased production of ITS-
relevant central systems and vehicle equipment needed for their deployment leading to an
increased turnover for the ITS sector in the EU. Additionally, the increased need for collecting
and making data available can lead to additional employment due to the need to install the
necessary equipment to facilitate this data collection and to operate the systems required to
distribute them. It may also lead to the need to deploy human resource to perform these actions.
The impact on employment generated can be expected to be larger as ITS service deployment
levels increase with the more intervening policy options. This analysis considers two
employment impacts calculated through different approaches:
 Direct employment impacts, that is, changes in employment in the sector that would
need to produce additional goods and services.
 Total employment impacts, including direct, indirect and induced impacts, which
reflect the economy-wide effects of changes in investment.87
The figures presented in Table 20 represent the average employment ranges (in FTEs)
generated from investments in ITS equipment and services, either directly or indirectly. This
is presented in average values for five-year periods. As seen in the table, the impacts of all POs
reaches its peak by 2035 as ITS deployment levels increase till that moment, in the years after
less investments in deployment are needed and costs are increasingly related to maintenance.
PO1 produces the least additional employment due to the lower investments induced by only
indirectly incentivising the deployment of ITS services, with the most important contributor
being the increased deployment of equipment in vehicles. These peak in the years between
2031-2035 at between 7,800 and 10,800 total FTEs out of which between 2,000 and 2,800 are
direct employment generated in the EU ITS sector. The employment generated by PO2 are
higher and total employment generated is estimated between 12,000 – 16,600 FTEs in the
period between 2031-2035. Out of these 3,000 - 4,100 FTEs are estimated to be the direct
employment generation in the ITS sector. This is boosted by the increased deployment of road-
side equipment necessary to facilitate the data availability mandates.
Table 20: Impacts on employment
Period PO1 PO2 PO3
Direct average employment (FTEs)
2025-2030 1,800 – 2,400 2,500 – 3,500 5,400 – 7,500
2031-2035 2,000 – 2,800 3,000 – 4,100 3,800 – 5,400
87
Total impacts include the changes in employment in the sectors that change their production, their suppliers,
suppliers of the suppliers, and the economy-wide employment effects caused by the additional employees
spending their wages on goods and services.
46
Period PO1 PO2 PO3
2036-2040 1,300 – 1,800 1,800 – 2,500 2,300 – 3,200
Total average employment (FTEs)
2025-2030 6,800 – 9,500 10,190 – 14,200 21,200 – 29,500
2031-2035 7,800 – 10,800 12,000 – 16,600 15,300 – 21,300
2036-2040 5,000 – 7,000 7,400 – 10,200 9,100 – 12,700
Source: Ricardo et al. (2021)
PO3 leads to the largest employment impacts, predominantly as a consequence of the C-ITS
equipment mandate for all new vehicles introduced. As the mandate is expected to come into
effect at 2028 for new vehicle models and 2030 for all new vehicles, the majority of additional
equipment costs incurred are expected to take place in the period leading up to its introduction.
This means that employment impacts can be expected to maximise in 2026-2030 and produce
a total employment impact of between 21.200 – 29,500 FTEs. The direct employment
generated in the ITS sector is expected to be at the level of 5,400 – 7,500 FTEs for the same
period. In all cases, as the vast majority of additional costs are expected to be in the area of
additional equipment deployed either in vehicles or in the form of RSIs, these ITS sectors can
be expected to see the lion’s share of the direct generated employment.
6.3. Environmental impacts
Impact on greenhouse gas emissions
Several of the services considered in this IA, such as green light optimal speed advisory, real
time information on congestion, roadworks or incidents, will contribute towards a reduced fuel
consumption and, in turn, lower CO2 emissions by improving traffic flow, reducing travel time
and increasing modal shift towards public transport and active modes. As shown in Table 21,
the model outputs give a reduction of CO2 emissions relative to the baseline for all three policy
options, with PO2 and PO3 have significantly greater benefits than PO1, particularly by 2040
when PO3 becomes fully effective.
The CO2 emission values have been monetised using the CO2 price from the 2019 Handbook
on external costs. When the present value of the cost of CO2 emissions savings are considered,
total benefits are also highest in PO3 with a saving of €2.4 billion between 2021 and 2040,
relative to the baseline. PO2 (€2.1 billion) has similar costs savings to that of PO3, while PO1
(€0.6 billion) is significantly lower. As with other impacts described in previous sections, the
more significant savings in PO2 and PO3 are driven by increased deployment which is a result
of the critical data and service mandates that are introduced. The costs savings associated with
each policy option are limited when put into the context of the baseline external costs.
Table 21: Annual CO2 emissions from road transport (million tonnes) – EU27
Year Mode Baseline PO1 PO2 PO3
2030
Annual CO2 emissions in 2030 522.6 522.1 520.2 520.0
Saving relative to the baseline in 2030 - 0.6 2.5 2.7
% savings relative to the baseline - 0.10% 0.50% 0.50%
2040
Annual CO2 emissions in 2040 168.9 168.4 167.7 167.0
Saving relative to the baseline in 2040 - 0.5 1.2 1.9
47
Source: Ricardo et al. (2021)
Impact on air pollutant emissions
Other emissions modelled include nitrous oxides (NOx), volatile organic compounds (VOC)
and particulate matter (PM) for all road transport. NOx emissions benefit from the same ITS
services and follow a similar trend to CO2 emissions, however Table 22 does not show as clear
a picture for VOC and PM. The annual VOC emissions increase in all policy options in 2030
and PM increases with increasingly intervening policy options.
Table 22: Annual pollutant emission savings for EU27 (tonnes)
2030 2040
Annual
emissions
Saving relative to
the baseline
% difference to
the baseline
Annual
emissions
Saving relative
to the baseline
% difference to
the baseline
Baseline
PM 50,447 - - 15,050 - -
NOx 885,687 - - 308,373 - -
VOC 67,457 - - 37,059 - -
PO1
PM 50,384 63 0.13% 14,998 53 0.35%
NOx 884,940 747 0.08% 307,733 640 0.21%
VOC 67,475 -18 -0.03% 37,048 11 0.03%
PO2
PM 50,425 23 0.05% 15,007 43 0.29%
NOx 884,136 1,550 0.18% 307,349 1,024 0.33%
VOC 67,568 -111 -0.16% 37,070 -11 -0.03%
PO3
PM 50,429 18 0.04% 15,027 24 0.16%
NOx 884,018 1,669 0.19% 307,108 1,265 0.41%
VOC 67,558 -101 -0.15% 37,051 8 0.02%
Source: Ricardo et al. (2021)
NOTE: negative values reflect an increase of emissions
The estimated impacts on PM and VOC emissions across the policy options are based on the
findings of the DRIVE C2X study concerning the impact of ‘in-vehicle speed limits’ (VSPD)
service under C-ITS V2I applications, showing an increase in PM and VOC emissions.88
They
found that the service would result in a smoother driving style on motorways, while on inter-
urban roads the increased braking or speed changes when approaching new speed limits would
result in increased PM and VOC emissions. The same study reported on the impact on NOx
emissions described above, but does not explain why the impacts differ between pollutants.
88
https://www.eict.de/fileadmin/redakteure/Projekte/DriveC2X/Deliverables/DRIVE_C2X_D11.4_Impact_A
ssessment_v1.0_full_version-1.pdf
% savings relative to the baseline - 0.30% 0.70% 1.10%
48
At the same time, no evidence was found that confirms this finding and green light optimal
speed advisory (GLOSA) – a similar type of service – has been reported to result in emission
reductions of these pollutants. Furthermore, it should be expected that a similar impact should
be expected in relation to NOx, but the study does not report on the reduction in NOx emissions.
Concluding, ITS services and particularly C-ITS services aim at smoother driving, which has
a positive effect on all emissions. Implementations that would not pre-empt speed changes (e.g.
only warning on the spot that the speed limit has changed) could however lead to increased
braking as one study has found, with a negative impact on some emissions. This highlights
how certain services, such as those that require speed reductions, can have different impacts
depending on the smartness of implementation (i.e. a heads-up on oncoming speed changes
should lead to smoother driving).
Despite the potential uncertainty around this impact on PM and VOC, the modelled impact is
very small, representing less than 0.35% for PM and less than 0.1% for VOC across the policy
options. Nevertheless, in 2040 all policy options are expected to bring emission savings, with
PO3 having the most significant impact. Cumulatively, the total air pollutant emissions
expected to be saved between 2021-2040 and the reduction in external costs of air pollution
(expressed as present value over 2021-2040) is greatest in PO3 with the PV benefits in PO2
also much greater than PO1 (see Table 23), although these improvements are dominated by
NOx and small overall, compared to the total emissions from road transport.
Table 23: Cumulative air pollutant emissions avoided (tonnes) relative to the baseline and the reduction in
external costs of air pollution, expressed as present value (EUR mn) for 2021-2040
PO1 PO2 PO3
Cumulative
emissions
avoided
Reduction in
external costs
of air pollution
Cumulative
emissions
avoided
Reduction in
external costs
of air pollution
Cumulative
emissions
avoided
Reduction in
external costs
of air pollution
PM 1,000 11.0 485 4.4 314 2.8
NOx 13,140 158.2 22,038 223.3 25,005 253.1
VOC -69 -0.1 -1,301 -1.3 -1,001 -1.1
Total 14,070 169.1 21,222 226.4 24,319 254.8
Source: Ricardo et al. (2021)
Impact on noise
Impacts on noise are a result of total transport activity. As the impacts of the policy options on
transport activity and modal shift are expected to be relatively limited, it is also expected that
any impacts on noise production will also be minimal. For more details see chapter 6.1. In
addition, smoother driving could also result in less noise but as described in the paragraphs
above such impacts face some uncertainty today and are expected to be smaller still.
7. HOW DO THE OPTIONS COMPARE?
7.1. Effectiveness
The effectiveness of the intervention is measured by the extent to which the specific and general
objectives of the policy intervention are addressed, or, as described in section 4.2, to what
49
extent the indicators of success are met. Table 24 gives a detailed analysis of the effectiveness
of each policy option, measured against those indicators. All in all, moving through the policy
options from PO1 towards PO3, a progressively improved achievement of the specific
objectives set for the ITS Directive can be observed.
Table 24: detailed comparison of policy options measured against assessment criteria linked to problem drivers
Indicator PO1 PO2 PO3
General Objective: Increase the deployment and (inter-)operational use of ITS services across the EU to
improve the functioning of a multimodal transport system and enhance interfaces between all modes
Deployment levels In 2040, 145mn equipped
vehicles, 111mn smart-
phone users of ITS services,
45k RSUs + 33k RSI + 159
TMCs
In 2040, 145mn equipped
vehicles, 196mn smart-
phone users of ITS
services, 45k RSU, 153k
RSIs, 402 TMCs
In 2040, 200mn equipped
vehicles, 193mn smart-
phone users of ITS
services, 156k RSUs, 196k
RSIs, 425 TMCs
Specific objective 1: Increase interoperability and cross-border continuity of ITS applications, systems and
services supporting a common ITS market
Increased financial
and administrative
capacity to
accelerated ITS
deployment
Increased coherence with
other legislation and
requirements for B2G
access to in-vehicle data
Data mandates impose
administrative capacity
increases
Service mandates impose
administrative capacity
increases
Increased
interoperability and
continuity of services
across Member States
Updates of priority areas
and increased coherence of
ITS Directive with other
initiatives such as TEN-T
Include deployment
mandates (data & services)
in scope of the Directive
(using common
specifications)
Standards for in-vehicle
generated data for road
operation + service
mandates for essential
services
Creation of common
standards, principles
and quality
requirements for
emerging ITS
services
Updates of priority areas,
requirements for B2G
access to in-vehicle data,
specifications for C-ITS,
coherence with other
legislation
Include deployment
mandates (data & services)
in scope of the Directive
(using common
specifications)
Standards for in-vehicle
generated data for road
operation
Increased
interoperability of
data generated by all
modes
Updates of priority areas Include deployment
mandates for data and
services in scope of the
Directive
Same as PO2
Specific objective 2: Establish a clear and effective coordination and concertation process for all ITS
stakeholders (including stakeholders relevant in the multimodal context of the Directive)
Stronger cooperation
in ITS governance,
industry buy-in
Further improve and
streamline interaction with
ITS stakeholders
Legal provisions on EU-
wide coordination of NAPs
Same as PO2
Comparable
monitoring of ITS
deployment across
MSs
Streamline reporting
obligations and mandate
common format & KPIs
Same as PO1 Same as PO1
Specific objective 3: Ensure improved data availability, access and quality standards used and facilitate the
exchange and usage of data supporting ITS services
Solutions for (trust)
issues with data
protection, privacy
and liability
Increased coherence with
other legislation and
initiatives such as TEN-T +
legal provisions on C-ITS
trust model
Same as PO1 Same as PO1
50
Indicator PO1 PO2 PO3
Increased incentives /
awareness to collect
and share ITS data
Update deployment
principles + increased
coherence with other
initiatives
Multiple data mandates
ensure data collection
Multiple service mandates
ensure data collection
Societal, economic and environmental benefits (all monetary values in present value 2021-2040)
Fuel consumption Limited impact. 0.16%
reduction in 2040 or -0.6bn€
compared to the baseline
Positive impact. 0.34%
reduction in 2040 or -2.1bn€
compared to the baseline
Very positive impact. 0.62%
reduction in 2040 or -2.4bn€
compared to the baseline
CO2 emissions Limited impact. 0.30%
reduction in 2040 or -0.6bn€
compared to the baseline
Positive impact. 0.70%
reduction in 2040 or -2.1bn€
compared to the baseline
Very positive impact. 1.10%
reduction in 2040 or -2.4bn€
compared to the baseline
Pollutant emissions –
PM, NOx, VOC
Limited, 0.17bn€ reduction
compared to the baseline
Limited, 0.23bn€ reduction
compared to the baseline
Limited 0,25bn€ reduction
compared to the baseline
Accidents Limited, 0.9% reduction in
2040 or -6.7bn€ compared
to the baseline
Moderate impact, 1.1%
reduction in 2040 or -
12.3bn€ compared to the
baseline
Very positive. 4.1%
reduction in 2040 or -
29.5bn€ compared to the
baseline
Travel time Moderate, 43.0bn€
reduction compared to the
baseline
Very positive, 138,8bn€
reduction compared to the
baseline
Very positive, 144,5bn€
reduction compared to the
baseline
PO2 and PO3 are expected to fulfil objective SO3 to a larger extent than PO1 with the
introduction of the data mandates. Additionally, PO3 also goes beyond what PO2 can achieve
against SO1, thanks to the introduction of service mandates and the development of standards
for in-vehicle data sharing. Finally, SO2 is already broadly fulfilled through the measures
streamlining ITS stakeholder coordination as introduced in PO1, however PO2 and PO3 go a
step further by institutionalising the NAP coordination mechanism. This assessment is
summarised in Table 25 below where it can be seen that PO3 is expected to achieve all SOs to
the largest extent.
Table 25: comparison of policy options on effectiveness
PO1 PO2 PO3
SO1: Increase interoperability and cross-border continuity of ITS applications,
systems and services supporting a common ITS market
+ +++ ++++
SO2: Establish a clear and effective coordination and concertation process for all
ITS stakeholders (including stakeholders relevant in the multimodal context of the
Directive)
++ ++(+) ++(+)
SO3: Ensure improved data availability, access and quality standards used and
facilitate the exchange and usage of data supporting ITS services
+ +++ ++++
Societal, economic and environmental benefits + +++ ++++
+: Indicate increases in the level of achievement of the specific objectives
(+): Indicate a minor increase in the level of achievement of the specific objectives
7.2. Efficiency
The efficiency is assessed by comparing the costs and benefits that have been monetized. Table
26 shows the main monetized costs and benefits associated with the policy options. Chapter
6.1 discusses additional administrative costs, but as their order of magnitude is millions,
compared to billions for other costs (see also the sensitivity analysis in chapter 7.5).
51
All policy options show net benefits and a positive cost benefit ratio. The many (light) policy
measures under PO1 result in net benefits at around €44 billion. Costs are expected to be
slightly higher under PO2 due to the mandate for data collection and the costs linked to
installing relevant equipment (i.e. RSUs and RSIs) but the respective benefits are three times
greater (mainly due to much greater time-related savings), leading to a net benefit of €145
billion, over three times higher than that of PO1. PO3 has even higher net benefits (€159
billion), mainly resulting from even higher benefits related to accident reduction, despite a
doubling of the costs (mainly related to in-vehicle systems) due to the mandate to fit new
vehicles with C-ITS equipment. The increased costs for new vehicles, render this policy option
less efficient than PO2, but it remains significantly more efficient than PO1 yielding more
benefits per cost unit required. The benefit-costs ratios vary significantly between all three
policy options but, unlike the net benefits, these are highly dependent on the uncertainties in
the cost estimates and the limitations of the modelling framework. On the other hand, for each
policy option additional benefits are expected from the deployment of MaaS and mobility
management services, which are currently not captured by the modelling exercise. As the costs
of these services are already included in the calculation, this means that an even more positive
cost to benefit ratio can be expected. Moreover, additional costs and benefits, not covered by
this assessment, can be expected from future ITS services (such as CCAM) that will be
facilitated by the ITS Directive revision (more in the sensitivity analysis in chapter 7.5).
Table 26: Costs and benefits of the policy options relative to the baseline for EU27, expressed as present value
over 2021-2040 (EUR bn)
PO1 PO2 PO3
Roadside units 0.2 0.2 1.1
Roadside infrastructure 0.9 3.2 3.3
National access points 0.1 0.4 0.4
Central ITS sub-systems 0.1 0.6 0.6
In-vehicle systems 6.2 6.2 15.4
Smartphone and applications 0.0 0.0 0.0
Total Costs 7.5 10.6 20.8
Reduction in external costs of accidents 6.7 12.3 29.5
Time saved 43.0 138.8 144.5
Reduction in external costs of CO2 emissions 0.6 2.1 2.4
Reduction in external costs of air pollutants 0.2 0.2 0.3
Fuel saving 0.6 2.1 2.4
Total Benefits 51.1 155.5 179.1
Total Net Benefits 43.6 144.9 158.3
Benefit/Cost ratio 6.8 14.7 8.6
Source: Ricardo et al. (2021)
As travel time savings are so significant it could be considered to build a policy option focusing
specifically on the measures that most influence them. However, all measures aim at tackling
issues that hinder the deployment of ITS, and all ITS contribute to reduced travel time (e.g.
measures aimed specifically at road safety also influence travel time as accidents in a highly
congested network often lead to complete gridlock). The opposite is also true but to a lesser
52
extent; measures aiming at improving travel time do not necessarily have a great influence on
road safety. Furthermore, though reduced travel time is clearly the biggest impact, the reduction
in external costs of accidents is also significant.
Reductions in fuel, CO2 emission and air pollutants may seem small in comparison but do not
yet include the potential benefits from multimodal mobility services as no reliable data on their
impact exists today. It is also impossible to estimate today to what extent automation will
accelerate the uptake of (shared) zero emission vehicles. These mid to long-term developments
have the potential to increase all benefits, tackle some of the negative externalities of transport
and contribute to its overall sustainability. It should also be noted that the baseline scenario
includes the ‘Delivering the European Green Deal’ and the pathway towards climate neutrality.
This translates into significant uptake of zero- and low-emission vehicles in the baseline that
limits the impact of the initiative on fuel use, CO2 emissions and air pollutant emissions.
Finally, unlike PO1, where uptake of ITS services is voluntary, PO2 and PO3 include
deployment mandates (for data and services respectively), making their impacts more certain.
7.3. Coherence
All developed policy options are coherent with the goals of the ITS Directive and broader
transport policies. PO2 scores significantly better than PO1 by ensuring the interoperability
and deployment of ITS services through data collection mandates, and thus increases the
certainty of achieving benefits relevant for overall transport policy goals. PO3 in addition
provides extra support to the continuity of services through the service mandates and
contributes greatly to Vision Zero, i.e. no road fatalities by 2050.
The revision of the ITS Directive specifically aims to tackle the problem driver of the limited
exchange and use of data. This is partially caused by stakeholder concerns regarding data
protection and privacy partially and the uncertainty regarding the coherence between the ITS
Directive and more recent pieces of the EU legal framework. All policy options aim to
specifically improve coherence with GDPR, ePrivacy Regulation and passenger rights rules
through the introduction of appropriate references to the provisions of these regulations. The
ITS Directive is thus introducing specific references to the requirements of the other existing
regulations and clarifies how potential sharing of data should comply with the framework
developed by already existing legislations (even without such provisions none of the policy
options affect the application of this legislation).
Table 27: Comparison of options on coherence
PO1 PO2 PO3
ITS Directive + ++ +++
Transport policies (e.g. Smart and Sustainable Mobility Strategy, Vision Zero) + ++ +++
GDPR, E-privacy & EECC proposals + + +
Overall coherence + ++ +++
Similarly, all policy options include measures intended to strengthen coherence with expected
upcoming legal instruments (i.e. Mobility Data Space, in-vehicle data architecture, TEN-T and
53
Rail Freight Corridors Regulation). Where the details of these regulations have been already
agreed, these POs are developed in a way that there is no overlap of contradiction in their
provisions. Where such details are not yet known, the relevant measures included in all policy
options foresee the need to align when those legal framework are more concretely designed.
7.4. Proportionality
PO1 relies on voluntary deployment and thus allows Member States and individual deployment
projects to decide whether or not to invest in ITS services. In this sense, PO1 is proportional to
achieving the intended objective.
PO2 imposes mandatory collection of crucial data. While it is a more stringent measure than
PO1, this will result in a significant uptake of ITS services based on that data and the expected
benefits, both direct and indirect, are also proportionally higher. In that sense, PO2 is
proportional.
PO3 imposes mandatory deployment of essential services, and an obligation on vehicle
manufacturers to equip all their new vehicle types with C-ITS stations. While some vehicle
models are already equipped, this policy option would make that mandatory for all new
vehicles since 2028. This is the most stringent measure but also the one that yields the highest
benefits, particularly on road safety and to a lesser extent on fuel efficiency and CO2 emissions.
In that sense, PO3 is proportional.
None of the policy options goes beyond what is necessary to achieve the main objective of ITS
services deployment and take-up. Progressively ambitious policy options are designed in order
to promote an increasing level of fulfilment of the specific objectives. The most intervening
policy options provide a reasonable period before mandates enter into force, and where this is
done, a phased coverage of the transport network is introduced considering the time needed to
organise the collection and sharing of the necessary data to support essential ITS services.
7.5. Summary of comparison of options, including stakeholder views
As described in more detail in chapter 5.3 the policy options are built incrementally, with the
more intervening measures split between PO2 and PO3. That means that PO1 already contains
a large amount of policy measures, which are widely supported by all stakeholders, not least
because amongst others they help future-proof the Directive and target improved stakeholder
concertation. So while all policy options address all specific objectives, in the following we
will see how the measures related to mandatory data collection (PO2) and mandatory service
provision (PO3) have a profound impact.
PO1 is significantly less effective as it lacks the more intervening measures that accelerate the
deployment and thus the usage of ITS services. PO2 is more effective but PO3 is most effective.
In addition, the mandates in PO2 and PO3 provide for the most certainty in achieving the
specific and overall objectives.
54
PO1 is least efficient and has significantly lower net benefits than other policy options. PO2
has the highest benefit-cost ratio at 14.7 but PO3 has the highest net benefits at 179.1b€ with a
significant 140% increase in road safety benefits for a total of 29.5b€.
All policy options are coherent with the objectives of the ITS Directive and have specific
measures to increase coherence with other legislation. The mandates included in PO2 however
increase the certainty of achieving benefits relevant for overall transport policy goals. This
applies even more for PO3, which is also most coherent with Vision Zero (i.e. zero road
fatalities by 2050)
All policy options are proportional, even the more stringent options, as the latter also generate
benefits matching their ambition and intervention level. In addition there is general agreement
amongst stakeholders on the scope of action needed and the options proposed. Nevertheless,
the biggest costs (those related to the mandates) trigger some reservations.
Particularly, on the mandatory collection of data, though nobody questions the identified
datasets nor the fact these are crucial, some Member States question the need to cover their
entire network, or the ambition level in terms of timeline. A phased approach, both in terms of
network coverage and timeline (starting for instance with data changes first, and providing a
comprehensive dataset later), is indeed justifiable and is already included in the IA. However,
the ambition should remain to deploy as fast as possible and, where relevant, cover the entire
network. Otherwise remote regions could end up being underserved, or even isolated, not just
from ITS but from mobility services altogether.
Similarly, the mandatory equipment of vehicles to deliver C-ITS services is well supported, in
terms of its relevance for road safety but also as a necessary enabler for higher levels of
automation. In addition strong synergies exist between such equipment and eCall (already
included in all vehicles since 2018), access to in-vehicle data (an ongoing initiative from DG
GROW, see also 5.2) and infotainment systems (expected to be prevalent in the timeline
envisaged by this initiative). Nevertheless, views diverge when addressing the technical details
and technologies to be included in such equipment. Those discussions are however outside the
scope of this initiative and impact assessment.
7.6. Sensitivity analysis
MaaS and mobility management services
Table 28: hypothesised benefits of MaaS and mobility management services
Scenario Distance class Reduction in transport time Reduction in transport costs
Low sensitivity
Short 3% 3%
Long 1.5% 1.5%
High sensitivity
Short 6% 6%
Long 3% 3%
Source: Ricardo et al. (2021)
To include the impact of MaaS and mobility management services, assumptions were made on
the potential improvements in travel time and travel cost of non-road trips. These potential
55
improvements were considered to be smaller in longer (non-urban national and international
trips), compared to shorter (urban and non-urban short trips), as can be seen in Table 28. Both
scenarios were then introduced and the impacts assessed in the ASTRA-TRUST model. The
majority of ITS services is targeted at improving road transport and not at fostering modal shift.
Those goals are not mutually exclusive but can lead to so-called rebound effects.
Table 29: modal shift including MaaS and mobility management services
Source: ASTRA / TRUST model
As can be observed in Table 29 MaaS and mobility management services (within the limits
imposed by the absence of reliable sources for their potential) can mitigate those rebound
effects from other ITS services, or even introduce a modal shift towards more sustainable
modes in the high sensitivity scenario. Furthermore, in the future ITS services are expected to
foster the deployment of mobility services based on highly automated vehicles. Such services
could (and indeed should) be fully integrated in a multimodal transport system, offering a
viable alternative to private vehicle ownership and have a far-reaching and positive impact on
the modal shift. Table 30 shows the full results of the analysis on all benefits. In the low
sensitivity run, total benefits increase by 11% relative to PO3, with comparable improvements
across each impact category.
Table 30: Overview of 2021-2040 present value for PO3 and the sensitivity runs for EU27 (EUR bn)
Cost / Benefit
PO3 -
Difference
relative to
the baseline
PO3 - sensitivity low PO3 - sensitivity high
Difference
relative to the
baseline
% change to
PO3
Difference
relative to
the baseline
% change to
PO3
Roadside units 1.1 1.1 0% 1.1 0%
Roadside infrastructure 3.3 3.3 0% 3.3 0%
National access points 0.4 0.4 0% 0.4 0%
Central ITS sub-systems 0.6 0.6 0% 0.6 0%
In-vehicle systems 15.4 15.4 0% 15.4 0%
Smartphone & applications 0.0 0.0 0% 0.0 0%
Total costs 20.8 20.8 0% 20.8 0%
Accident reduction benefits 29.5 32.3 9% 42.8 45%
Time saved benefits 144.5 161.2 12% 194.6 35%
CO2 emission benefits 2.4 2.8 15% 4.1 69%
Other emissions benefits 0.3 0.4 40% 0.7 179%
Fuel saving benefits 2.4 2.8 15% 4.1 69%
Total benefits 179.1 199.4 11% 246.3 38%
Total net benefits 158.3 178.6 13% 225.5 42%
Benefit/Cost ratio 8.6 9.6 n/a 11.8 n/a
Source: ASTRA / TRUST
Year Mode Baseline PO1 PO2 PO3 PO3 low PO3 high
2030 Car 80.2% 80.2% 80.5% 80.5% 80.3% 80.0%
Bus 9.4% 9.4% 9.2% 9.2% 9.3% 9.5%
Train 10.5% 10.4% 10.3% 10.3% 10.4% 10.5%
2040 Car 79.9% 80.0% 80.3% 80.2% 80.0% 79.7%
Bus 9.0% 8.9% 8.8% 8.8% 9.0% 9.2%
Train 11.1% 11.1% 10.9% 10.9% 11.0% 11.2%
56
Total net benefits increase by 13% to €179 billion. In the high sensitivity run, total benefits
increase by 38%, while total net benefits increase by 42% to €226 billion. In both cases,
additional benefits are driven mainly by increased time savings as a direct result of the use of
more efficient multimodal and mobility management services. The modal shift potential of
these services is also expected to lead to safety benefits as safer modes can be expected to be
increasingly used in the context of multimodal transport. Fuel savings and CO2 emission gains
are lesser contributors to the increased benefits estimated in this sensitivity runs.
At the same time, the total costs induced by PO3 remained the same in both scenarios as the
additional costs of these services where already introduced in the initial assessment of impacts.
All in all, the sensitivity analysis indicates that even if there are only moderate benefits from
the increased deployment of MaaS and mobility management services, the performance of PO3
can be expected to improve and yield considerable additional benefits.
Cost sensitivity analysis
There is a relatively high degree of accuracy on the per unit cost inputs. However, the
translation of ITS infrastructure deployment assumptions into service deployment and
ultimately service usage involves additional calculation steps and assumptions, introducing
more uncertainty. In particular, engagement with stakeholders has highlighted particular
challenges around projecting the number of RSUs and RSIs required89
. Furthermore, as
discussed in chapter 6.1, relevant stakeholders have pointed to the high potential cost burden
that may fall on the public sector (including road authorities) for data collection, processing
and making data available to support ITS services. These three key steps can each entail
activities at either the national or local level, although collecting data and estimating costs on
each is challenging as different institutional set-ups of authorities exist in every Member State.
Some relevant examples were identified, for example the city of Gothenburg spent a total of
300k€ over three years to digitize its traffic regulations90
, while the Dutch transport ministry
spends 10m€ yearly on data collection and operation of a national data warehouse, which also
hosts the National Access Point91
. The support study for the revision of the Delegated
Regulation on real-time traffic information92
, which is most relevant for this IA, estimates a
present value (2021-2030) of costs from a partial data collection mandate for the EU28 at
€18m93
. This includes personnel cost for data collection, processing and maintenance for RTTI
data as well as costs for coordination, standardization and training activities. To cover the large
variations in these cost elements, a sensitivity analysis on costs of ITS infrastructure
deployment has been developed and applied to PO3.
89
Stakeholder feedback during the workshop highlighted the uncertainty and differences in opinion surrounding
the likely scale and location of RSU deployment.
90
Information provided by city authorities and compiled by Polis for Ricardo as part of the IA support study
91
Source: Interview with Netherlands Ministry of Infrastructure and the Environment, carried out in April 2021
by Ricardo
92
https://op.europa.eu/en/publication-detail/-/publication/043ee22b-643b-11eb-aeb5-01aa75ed71a1
93
Ricardo’s own analysis of data used to support calculated from support study for the revision of the Delegated
Regulation on real-time traffic information, recharging/refuelling points; and access to vehicle data for road
operation purposes.
57
In the first scenario (‘cost sensitivity 1’), all costs are increased by 50%, while in the second
(‘cost sensitivity 2’) the costs burden on the components related to data collection and
processing94
are increased by a further 50% (100% in total). Table 31 shows that under each
scenario, the net present value of benefits in PO3 does not decrease significantly. Despite a
significant increase in total costs from 20.3 billion EUR to 31.2 billion EUR in sensitivity run
2, the strong net benefit highlights the robustness of the model results to cost increases.
Moreover, in all sensitivity runs, the benefits to cost ratio of the policy options remains positive.
Table 31: Overview of 2021-2040 present value of the costs, benefits, and net benefits for the cost sensitivity
cases relative to the baseline for EU27 - with and without the cost sensitivities applied (EUR bn)
PO3 Cost sensitivity 1 Cost sensitivity 2
Roadside units 1.1 1.7 2.2
roadside infrastructure 3.3 4.9 6.5
National access points 0.4 0.6 0.8
central ITS sub-systems 0.6 0.9 1.2
In-vehicle systems 15.4 23.1 23.1
Smartphone and applications 0.0 0.0 0.0
Total costs 20.8 31.2 33.8
Total Benefits 179.1 179.1 179.1
Total net benefits 158.3 147.9 145.3
Benefit/Cost ratio 8.62 5.75 5.29
8. PREFERRED OPTION
8.1. Policy option 3: Mandating provision of essential services
PO2 is preferred over PO1, as it achieves significantly larger benefits and has the highest cost
benefit ratio. The mandatory collection of data and the resulting uptake of ITS services greatly
increases its effectiveness in achieving the objectives of the ITS Directive and makes it more
coherent. Limiting the mandatory collection of data to crucial data and the very significant
resulting benefits also mean it is proportional.
The difference in net benefits between PO2 and PO3 is smaller than the difference between
PO1 and PO2, but they remain very significant and constitute a considerable increase in safety
related benefits (29,5b€ or 140% higher in PO3 than PO2). The benefit-to-cost ratio of the
additional measures in PO3 (in other words comparing only the additional costs and benefits)
is lower than that of the measures in PO2, but is still positive at 2.5. In other words, the service
mandates and related equipment proposed in option 3 are, also when evaluated separately, a
good investment. Furthermore, the same equipment can be used to deliver ever more advanced
C-ITS services, increasing the benefits at no extra cost, which is likely already the case by the
time this measure enters into force. Option 3 is also the most coherent option and through the
accelerated deployment of C-ITS is the one that best prepares for higher levels of automation
by connecting vehicles with each other. This in turn would give the European automotive and
ITS industry an advantage, leading to higher levels of new business opportunities and job
creation, and more significant research and innovation impacts. Lastly, the mandatory
94
Including roadside infrastructure, data collection and central sub-system costs.
58
provision of essential ITS services for road safety, despite considerable compliance costs, is
also proportional.
So while PO2 scores higher on benefit-cost ratio, PO3 comes out on top on all other criteria
and is thus the preferred policy option. More particularly, it generates the highest net benefits,
is the most effective option, best prepares for a more automated future, best achieves the
specific objectives of the ITS Directive and best ensures the swift and coherent deployment of
ITS services, in line with the objectives of the Smart and Sustainable Mobility Strategy.
Finally, as the policy options are built incrementally, all measures that generate the high
benefit-cost ratio of PO2 are included in the preferred option.
8.2. REFIT (simplification and improved efficiency)
REFIT Cost Savings – Preferred Option(s)
Description Amount Comments
Update and streamline reporting obligations Not
quantified
Recurrently reduces administrative costs of
Member States
Mandate reporting based on common format &
KPIs
Not
quantified
Recurrently reduces administrative costs of
Member States
Improve the coherence of the ITS Directive with
the existing legal framework (e.g. GDPR)
Not
quantified
Reduces administrative and compliance costs of
all stakeholders that deploy ITS services
Improve the coherence of the ITS Directive with
expected initiatives (e.g. TEN-T Regulation)
Not
quantified
Reduces administrative and compliance costs of
all stakeholders that deploy ITS services
9. HOW WILL ACTUAL IMPACTS BE MONITORED AND EVALUATED?
Monitoring and evaluation should build on a simple approach that is transparent and easily
accessible. It is not the intention to create a very complex and complicated system of KPIs,
noting that Member States reports transmitted every 3 years to the Commission should
themselves already include KPIs that allow the monitoring of the deployment of ITS services
and of the availability and accessibility of data on the NAPs. Current KPIs for reporting should
be updated (and made mandatory when relevant) to better allow this monitoring.
More specifically, the Commission services will monitor the implementation and effectiveness
of this initiative through a set of core indicators that will measure the progress towards
achieving the specific objectives, based on the measures that are part of the preferred option
PO3. Some of the indicators are of a qualitative nature and show if the desired deliverables are
being achieved and implemented, while others are based on data to be collected that will need
to be analysed further.
Specific objective Progress indicators Source of data
Increase interoperability and
cross-border continuity of ITS
applications, systems and services
supporting a common ITS market
 KPIs95
on the deployment of ITS services,
including services mandated by the proposal.
 Qualitative assessment of the ITS activities of
public and private stakeholders.
 Member
State reports
 CEF-funded
projects
Establish a clear and effective
coordination and concertation
 Number of meetings and level of participation
from all public and private stakeholder categories.
 Commission
95
List of KPIs available on https://ec.europa.eu/transport/themes/its/road/action_plan/its_national_reports_en
59
Specific objective Progress indicators Source of data
process for all ITS stakeholders
(including the multimodal
context)
 Number of coordination projects (CEF, DEP) and
participating stakeholders
Ensure improved data availability,
access and quality standards to
facilitate the exchange and usage
of data supporting ITS services
 KPIs for data availability and accessibility on
NAPS, including mandated data.
 Qualitative assessment of the ITS activities of
public and private stakeholders.
 Member
State reports
Considering that ITS is a fast-moving sector, it is foreseen that the Commission services will
report to EP and Council every 3 years on the implementation of the Directive and its Delegated
Acts, taking into account the analysis of national reports on ITS deployment (MS also report
to the Commission every three years). This is intended to determine whether the measures in
place have resulted in an improvement of the situation and to verify whether the objectives of
the initiative have been reached. This reporting shall be carried out based on the core progress
indicators below, in line with Commission requirements on evaluation, and will be part of the
report that the Commission shall submit every three years to the European Parliament and to
the Council on the progress made for the implementation of the Directive.
60
Annex 1: Procedural information
1. LEAD DG, DeCIDE PLANNING/CWP REFERENCES
The lead DG is Directorate General for Mobility and Transport (MOVE), Unit B4, Sustainable
& Intelligent Transport.
DECIDE reference number: PLAN/2020/7429 - Revision of the Intelligent Transport Systems
Directive, planned adoption data Q4 2021.
The development of this initiative was announced under item A 4 a) in Annex 1 to the
Commission Work Programme 202196
and under action 38 of the Sustainable and Smart
Mobility Strategy97
. The Inception Impact Assessment was published on 8 October 202098
.
2. ORGANISATION AND TIMING
The Inter Service Steering Group (ISSG) for the impact assessment on the revision of Directive
2010/40/EU ("ITS Directive") was set up in July 2020 and included the following DGs and
Services: SG, SJ, CLIMA, CNECT, COMP, ENER, ENV, FISMA, GROW, JRC, JUST,
REGIO, RTD, SANTE.
In total, 5 meetings of the ISSG were organised to discuss the impact assessment. These
meetings took place on 2 September 2020, 15 December 2020, 4 March 2021, 17 June 2021
and 23 July 2021 (all virtual meetings). Further consultations with the ISSG were carried out
by e-mail.
The ISSG approved the Impact Assessment roadmap, the Terms of Reference for the External
Support Study and the questionnaire for the Open Public Consultation and discussed the main
milestones in the process, in particular the different deliverables of the support study.
3. CONSULTATION OF THE RSB
The Regulatory Scrutiny Board will receive the draft version of the impact assessment report
by 25 August 2021. The Board meeting will take place on 22 September 2021.
4. EVIDENCE, SOURCES AND QUALITY
The starting point for the drafting of the impact assessment was the evaluation of the ITS
Directive.99
Information provided by the stakeholders through the stakeholder consultation
activities were an important source of information (see Annex 2). It was completed by
information provided ad hoc by different stakeholders to the Commission.
96
https://ec.europa.eu/info/publications/2021-commission-work-programme-key-documents_en
97
https://eur-lex.europa.eu/resource.html?uri=cellar:5e601657-3b06-11eb-b27b-
01aa75ed71a1.0001.02/DOC_2&format=PDF
98
https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12534-Intelligent-transport-systems-
review-of-EU-rules-_en
99
Ex-post evaluation of the Intelligent Transport Systems Directive 2010/40/EU - SWD(2019) 369
61
The Commission sought external expertise through a contract for a support study with
RICARDO Nederland B. V, supported by Ricardo-AEA Limited, TRT and M-Five, which was
launched in November 2020. The findings of the impact assessment report build on the final
report from this contract.
Overall, the sources used for the drafting of the Impact Assessment report are numerous,
diverse and representative of the different stakeholder groups.
62
Annex 2: Stakeholder consultation
1. INTRODUCTION
In the context of the preparation of the Impact Assessment, various stakeholder consultation
activities were carried out. Consultation activities sought both qualitative (opinions, views,
suggestions) and quantitative (data, statistics) information. Some of these activities were part
of the Impact Assessment support study (by an external contractor, RICARDO), which was
launched in November 2020.
This annex provides an overview of the stakeholder groups that were consulted as well as a
summary and analysis of the responses received. The consultation covered all aspects of the
Impact Assessment (problem definition, EU dimension, options and potential impacts).
The consultation process100
engaged main target groups through different methods, combining:
 Publication of the Inception Impact Assessment (IIA), and a request for submission of
comments to the IIA by all interested stakeholders which ran from 8 October 2020 until
19 November 2020.
 An Open Public Consultation (OPC) was launched on 3 November 2020 and remained
open until 2 February 2021
 Targeted consultation
o An online survey for all key stakeholder groups was launched on 15 February
2021 and remained open until 26 March 2021
o An interview programme with 53 stakeholders from all key stakeholder groups
was launched on 16 February 2021 and remained open until 6 May 2021.
Furthermore, six exploratory interviews with key stakeholders were conducted
in the inception phase of the study (November/December 2020)
 Six stakeholder workshops that took place between December 2020 and June 2021.
 Meetings of the ITS Committee on 17 December 2020 and 28 June 2021
Throughout the period of preparing the Impact Assessment, Commission services have
additionally met with a wide variety of stakeholders, and received several position papers.
100
More detail can be found in Annex F of the support study
63
2. CONSULTATION METHODS
Publication of the Inception Impact Assessment
The Inception Impact Assessment101
for the initiative was published on 8 October 2020 and
was open for feedback until 19 November 2020. In the IIA, the Commission identified three
‘key problem drivers’, i.e., that there was:
 A lack of interoperability and continuity of applications, systems and services;
 A lack of concertation and effective stakeholder coordination; and
 Unresolved issues related to the availability and sharing of data supporting ITS
services.
Thirty-four responses were received through the feedback mechanism and an additional two
by mail, however some were related contributions (supporting documents or longer versions
of the responses provided in the survey) and there was one repeat response.
Figure 15: Summary of responses by stakeholder type (number and % of responses)
The responses were generally favourable of the initiative and many respondents either set out
their views in each of these areas or focused on one of these in particular. The initial intention
had been to present the responses according to these three problem drivers followed by other
issues that had been mentioned. However, after having reviewed the responses it was clear that
many would lose their coherence if they were presented in this way. The exception to this was
101
https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12534-Intelligent-transport-systems-
review-of-EU-rules-_en
64
in relation to the third key problem driver relating to data availability and sharing, which was
the focus of nine responses, although this issue was covered to some detail in many responses.
Open Public Consultation (OPC)
The Open Public Consultation was launched on the Commission website on 3 November 2020
and was open for responses until 2 February 2021 (13 weeks).102
The questionnaire for the
consultation was prepared by DG MOVE, together with the members of the steering group and
the consultant for the support study. It invited stakeholders' opinions on the key elements of
the Impact Assessment: the main problems, their drivers, possible policy measures and their
likely impacts and the relevance of EU level action. The consultant summarised the results of
the public consultation in a detailed report.103
The OPC received 149 responses, of which only 4 respondents were based outside the EU.
Figure 16: Geographical distribution of responses received
Country of
origin
Number of
responses
% of responses Country of origin Number of
responses
% of
responses
Belgium 38 25.5% Poland 4 2.7%
Germany 29 19.5% Greece 2 1.3%
France 21 14.1% Ireland 2 1.3%
Sweden 11 7.4% Luxembourg 1 0.7%
Finland 8 5.4% Denmark 1 0.7%
Austria 7 4.7% Malta 1 0.7%
Italy 6 4% Norway 1 0.7%
Netherlands 5 3.4% Switzerland 1 0.7%
Czechia 4 2.7% Israel 1 0.7%
Spain 4 2.7% China 1 0.7%
Figure 17: Classification and number of stakeholders responding to the OPC
Stakeholder group Number of responses % of responses
Academic/research institution 3 2%
Business association 37 24.8%
Company/business organisation 46 30.9%
Environmental organisation 1 0.7%
Consumer organisation 3 2%
EU citizen 12 8.1%
Non-governmental organisation 12 8.1%
Public authority 22 14.8%
Trade union 1 0.7%
102
https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12534-Intelligent-transport-systems-
review-of-EU-rules-/public-consultation_en
103
Included in annex F of the support study
65
Stakeholder group Number of responses % of responses
Other 11 7.4%
Targeted consultation
The following key and relevant stakeholder groups were targeted:
 EU Public bodies (including European institutions, standardisation bodies,
international organisations and public banks).
 Public authorities and other (including ministries within Member States and regions,
as well as organisations that represent city and regional networks).
 Industry stakeholders (including ITS service providers, ITS organisations,
infrastructure managers, mobility service providers, digital map providers, vehicle
manufacturers and their suppliers, technology and telecommunication suppliers, and
public transport).
 Civic Society and research (including consumer bodies, disability and elderly
advocacy groups, research organisations with specific ITS expertise and organisations
that represent transport employees and trade unions).
Whilst both the survey and interviews overlapped in thematic areas, the questions asked had a
slightly different focus with the survey focussing more on collecting quantitative information,
and the interviews focussing more on qualitative inputs.
Online survey
An online survey104
was launched on 15th
February 2021. The survey focused on obtaining
input on the expected impacts (economic, social and environmental) of the measures under
consideration in comparison to the baseline, the possible issues that may arise, to help assess
the level of support for specific measures, and where relevant, input on the cost implications
of each measure.
In order to reach a wide audience, the support of relevant umbrella organisations (including
ERTICO-ITS, MaaS Alliance, CEDR, ACEA and UITP) which shared the survey
questionnaire with their members, was relied upon.
The survey was in English and remained open for a period of six weeks (15/02/21-26/3/2021)
using the online platform Alchemer. A total of 36 responses were received. Of these, four also
took part in an interview, three participated in the IIA, and eight completed the OPC. 24 unique
stakeholders took part only in the survey.
In-depth interviews
104
https://survey.alchemer.eu/s3/90315608/Survey-Impact-Assessment-on-the-revision-of-the-Directive-on-
Intelligent-Transport-Systems-2010-40-EU
66
Six exploratory semi-structured interviews were initially undertaken with selected
stakeholders during the inception phase of the study. They included:
 ACEA - European Automobile Manufacturers’ Association
 POLIS - Network of European Cities and Regions
 AustriaTech - Company of the Austrian Federal Government dealing with
developments in mobility and technology
 CEDR - Organisation of European National Road Administrations
 UITP - International Association of Public Transport
 ASECAP - European Association of Operators of Toll Roads
The purpose of the exploratory interviews was to assist in refining the problem definition and
the policy options, as well as supporting developing the field research tools. More specifically,
these interviews assisted in ensuring that all issues that could be relevant to the problem
definition and the definition of the policy options were correctly identified early in the process,
as well as supporting in identifying all relevant information sources for the study. Furthermore,
the topics discussed in the interviews contributed to the design and development of the draft
survey questions and interview guides.
The main interview programme ran between 16 February and 6 May 2021. Just like the survey,
the aim of the interviews was to allow discussing impact assessment parameters and to validate
the choice of policy measures (following initial screening) and policy options (following the
initial packaging). They focused on obtaining detailed input on the expected impacts
(economic, social and environmental) of the measures under consideration in comparison to
the baseline, the possible issues that may arise and to identify the level of support for specific
measures, and, where relevant, the cost implications of each measure.
A total of 53 main interviews (plus the six exploratory interviews), were undertaken with
stakeholders during the study. Of the stakeholders involved, four also took part in the survey,
16 participated in the IIA, and 30 completed the OPC. 22 unique stakeholders took part only
in the interviews.
The table below outlines the interviews conducted and responses received to the online survey,
as well as the total number of unique stakeholders involved in the targeted consultation.
Type of stakeholder Number of interviews
conducted
Number of respondents to
the online survey
Total number of individual
stakeholders participated
Public bodies 5 (+1 exploratory) 3 8
Public authorities and
other public bodies
18 (+2 exploratory) 10 27
Industry and associations 23 (+3 exploratory) 19 40
Civic society 7 4 11
TOTAL 59 36 86
Stakeholder workshops
67
A series of six workshops were organised to support the impact assessment.
Workshop Date Objectives Type of workshop No. of registered
participants
1 15
Decembe
r 2020
 Overview of proposed study,
including methodology
 Overview of IIA responses
 Discussion on definition of main
problems
Open for all
interested
stakeholders
285
2 14
January
2021
 Validation of key data and
assumptions related to specific
problem areas with technical
experts
Restricted to
stakeholders/experts
with a technical
background
18
3 19
January
2021
 Validation of key data and
assumptions related to specific
problem areas with legal and
policy experts
Restricted to
stakeholders/ experts
with a legal and/or
policy background
26
4 3 March
2021
 Overview of study progress to date
 Summary of OPC responses
 Presentation and discussion on
proposed policy options
Open with separate
sessions restricted to
selected participants
identified from initial
registration
310
5 14 April
2021
 Presentation of the high-level
impact assessment methodology to
validate intervention logic and key
assumptions
Restricted to
stakeholders with an
expertise in policy
assessments
25
6 24 June
2021
 Presentation of the draft final
results from the impact assessment
 Gathering feedback on the
preferred policy option, including
on legal, political and technical
feasibility to inform the final report
Open for all
interested
stakeholders
202
68
Annex 3: Who is affected and how?
1. PRACTICAL IMPLICATIONS OF THE INITIATIVE
The deployment of ITS services can be expected to lead to a number of benefits for various
stakeholders. The impacts of specific services across a number of impact indicators
including time and congestion savings, fuel efficiency, emissions reduction and transport
safety are elaborated in Annex 3. In summary, it can be concluded that the lagging
deployment of ITS services is expected to affect the following stakeholder categories:
 Transport service users first and foremost as they will be able to use more advanced
ITS services or will enjoy only partial and delayed benefits. Missed benefits will
include travel cost and time reductions, safety benefits and improved quality of
transport services extending all modes of transport that would be expected to be
produced by various ITS services.
 Member States and local authorities are also expected to miss out on the benefits of
improved traffic management while the fragmented, uneven and discontinuous
deployment of ITS services may also incur increased deployment costs. It will also be
detrimental to road operators and traffic managers, who will have less access to new
solutions to more efficiently manage their networks.
 ITS service providers (including micro-mobility service providers), vehicle
manufacturers and other service providers that rely on equal access and availability of
qualitative data to provide their services can be also expected to be significantly
affected in their capacity to develop and offer services at optimal cost and quality
levels.
 Society as a whole is expected to miss out on the expected reduction of traffic safety
incidents, congestion and other external costs of transport, achieved by better traffic
management, improved transport system performance and the promotion of a modal
shift towards public transport and active mobility modes. In addition, this creates costs
of emergency services, health care costs and production losses.
 It would also put the European automotive and ITS industry at a disadvantage
compared to its competitors, leading to lower levels of new business opportunities in
the digitalisation of transport along with lower levels of job creation, and less
significant research and innovation impacts on the overall European economy. As the
jobs of millions of Europeans depend directly or indirectly on the automotive and wider
transport industries, it is critical that the sector is provided with the conditions to keep
up with global market players.
 The telecom sector is also affected as C-ITS and CCAM services can use their cellular
network and technologies to deliver services and this can thus constitute a new growth
market.
2. SUMMARY OF COSTS AND BENEFITS
I. Overview of Benefits (total for all provisions) – Preferred Option
Description Amount Comments
Direct benefits
Reduction of travel time
relative to the baseline
€144.5 billion The effect of the reduction of travel time resulting from the
deployment of ITS services that improve transport efficiency
69
I. Overview of Benefits (total for all provisions) – Preferred Option
Description Amount Comments
(i.e. present value 2021-
2040)
(and indirectly from the deployment of ITS services that improve
road safety as accidents can create significant delays in a
saturated transport system). The reduction of travel time is
estimated at around €144.5 billion relative to the baseline over
the 2021-2040 period, expressed as present value.
Reduction of fuel
consumption (i.e. present
value 2021-2040)
€2.4 billion It is the effect of the reduction of fuel consumption resulting from
the deployment of ITS services that improve transport efficiency.
The reduction of fuel consumption is estimated at around €2.4
billion relative to the baseline over the 2021-2040 period,
expressed as present value.
Indirect benefits
Reduction of external
costs related to road
safety (i.e. present value
2021-2040)
€29.5 billion Indirect benefit to society at large. It is the effect of the reduction
of accidents resulting from the deployment of ITS services that
improve road safety. The reduction includes fatalities, serious
and minor injuries and their external costs is estimated at around
€29.5 billion relative to the baseline over the 2021-2040 period,
expressed as present value.
Reduction of external
costs related to CO2
emissions relative to the
baseline (i.e. present
value 2021-2040)
€2.4 billion Indirect benefit to society at large. It is the effect of the reduction
of CO2 emissions resulting from the deployment of ITS services
that improve transport efficiency. The reduction in the external
costs of CO2 emissions is estimated at around €2.4 billion relative
to the baseline over the 2021-2040 period, expressed as present
value.
Reduction of external
costs related to air
pollution emissions
relative to the baseline
(i.e. present value over
2021-2040)
€0.3 billion Indirect benefit to society at large. It is the effect of the reduction
of air pollution emissions resulting from the deployment of ITS
services that improve transport efficiency. The reduction in the
external costs of air pollution emissions is estimated at around
€0.3 billion relative to the baseline over the 2021-2040 period,
expressed as present value.
Innovation /
competitiveness in the
mobility sector
Provisions for static and dynamic transport data on national (and
common) access points of Member States will foster an ITS
market that will contribute to the development of new innovative
services that foster a more inclusive multimodal mobility system.
Such commonly available and accessible data can particularly
benefit service innovation and other innovation, including by
SMEs. It is also expected to play a strong enabling role in the
development of the emerging and highly competitive field of
CCAM.
Moreover, standardisation of interoperability of data and services
will enable better innovative service development which will
finally benefit all transport users.
II. Overview of costs – Preferred option
Citizens/
Consumers
Businesses Administrations
One-
off
Re-
current
One-
off
Re-
current
One-off Recurrent
Investments related
to the equipment of
(roadside and
central)
Direct
costs
RSU:
€0.8 bn
RSI:
Maintenance and operation costs
Road-side units: €0.3 bn
Road-side infrastructure: €0.3 bn
70
II. Overview of costs – Preferred option
Citizens/
Consumers
Businesses Administrations
One-
off
Re-
current
One-
off
Re-
current
One-off Recurrent
infrastructure in
support of ITS
services
€2.9 bn
NAP:
<€0.1 bn
National access points: €0.4 bn
Compliance costs
related to the
equipment of
vehicles with
dedicated
equipment in
support of ITS
services
Direct
costs
€10.5
bn
€4.9
bn
Administrative
costs related to the
digitalisation of
public transport
data and monitoring
costs
Direct
costs
The costs to public authorities
from the requirements to review
and update the national policy
frameworks (NPFs) and report on
the implementation are similar as
in the baseline. Monitoring costs
may increase to some extent to
report on compliance with the
mandatory provision of crucial
data and essential services. The
additional costs relative to the
baseline can’t be quantified. The
provision of standardised data
formats, common reporting
format supported by common
reporting KPIs and alignment of
reporting requirements (from
Delegated Regulations and
Directive) will simplify overall
reporting under the Directive.
71
Annex 4: Analytical methods
1. DESCRIPTION OF THE MODELLING TOOL USED
The analytical framework used for the purpose of this impact assessment builds on the
PRIMES-TREMOVE, ASTRA and TRUST models, complemented by the assessment of
ITS deployment and cost and benefit analysis, drawing on the impact assessment support
study.105
The baseline scenario has been developed using the PRIMES-TREMOVE model by
E3Modelling. PRIMES-TREMOVE has a successful record of use in the Commission's
energy, transport and climate policy assessments. In particular, it has been used for the
impact assessments underpinning the ‘Fit for 55’ package, the impact assessments
accompanying the 2030 Climate Target Plan 106
and the Staff Working Document
accompanying the Sustainable and Smart Mobility Strategy107
, the Commission’s proposal
for a Long Term Strategy108
as well as for the 2020 and 2030 EU’s climate and energy
policy framework.
ITS deployment has been assessed by Ricardo in the context of the impact assessment
support study. ASTRA and TRUST are the main models used to assess the impacts of the
policy options presented in this impact assessment, drawing on the ITS deployment. The
assessment with the ASTRA and TRUST models has been undertaken by TRT. For the
baseline scenario ASTRA and TRUST models have been calibrated on the results of the
PRIMES-TREMOVE model.
PRIMES-TREMOVE model
The PRIMES-TREMOVE transport model projects the evolution of demand for
passengers and freight transport, by transport mode, and transport vehicle/technology,
following a formulation based on microeconomic foundation of decisions of multiple
actors. Operation, investment and emission costs, various policy measures, utility factors
and congestion are among the drivers that influence the projections of the model. The
projections of activity, equipment (fleet), usage of equipment, energy consumption and
emissions (and other externalities) constitute the set of model outputs.
The PRIMES-TREMOVE transport model can therefore provide the quantitative analysis
for the transport sector in the EU, candidate and neighbouring countries covering activity,
equipment, energy and emissions. The model accounts for each country separately which
means that the detailed long-term outlooks are available both for each country and in
aggregate forms (e.g. EU level).
In the transport field, PRIMES-TREMOVE is suitable for modelling soft measures (e.g.
eco-driving, labelling); economic measures (e.g. subsidies and taxes on fuels, vehicles,
105
Ricardo et al. (2021), Impact Assessment Support Study for the revision of the Intelligent Transport
System Directive (2010/40/EU), Study contract no. MOVE/B4/SER/2020-230
106
SWD/2020/176 final.
107
https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020SC0331
108
https://ec.europa.eu/clima/sites/clima/files/docs/pages/com_2018_733_analysis_in_support_en_0.pdf
72
emissions; ETS for transport when linked with PRIMES; pricing of congestion and other
externalities such as air pollution, accidents and noise; measures supporting R&D);
regulatory measures (e.g. CO2 emission performance standards for new light duty vehicles
and heavy duty vehicles; EURO standards on road transport vehicles; technology standards
for non-road transport technologies, deployment of Intelligent Transport Systems) and
infrastructure policies for alternative fuels (e.g. deployment of refuelling/recharging
infrastructure for electricity, hydrogen, LNG, CNG). Used as a module that contributes to
the PRIMES model energy system model, PRIMES-TREMOVE can show how policies
and trends in the field of transport contribute to economy-wide trends in energy use and
emissions. Using data disaggregated per Member State, the model can show differentiated
trends across Member States.
The PRIMES-TREMOVE has been developed and is maintained by E3Modelling, based
on, but extending features of, the open source TREMOVE model developed by the
TREMOVE109
modelling community. Part of the model (e.g. the utility nested tree) was
built following the TREMOVE model. 110
Other parts, like the component on fuel
consumption and emissions, follow the COPERT model.
Data inputs
The main data sources for inputs to the PRIMES-TREMOVE model, such as for activity
and energy consumption, comes from EUROSTAT database and from the Statistical
Pocketbook "EU transport in figures111
. Excise taxes are derived from DG TAXUD excise
duty tables. Other data comes from different sources such as research projects (e.g.
TRACCS project) and reports.
In the context of this exercise, the PRIMES-TREMOVE transport model is calibrated to
2005, 2010 and 2015 historical data. Available data on 2020 market shares of different
powertrain types have also been taken into account.
ASTRA model
ASTRA is a strategic model based on the Systems Dynamics Modelling approach
simulating the transport system development in combination with the economy and the
environment until the year 2050.
109
Source: https://www.tmleuven.be/en/navigation/TREMOVE
110
Several model enhancements were made compared to the standard TREMOVE model, as for example:
for the number of vintages (allowing representation of the choice of second-hand cars); for the technology
categories which include vehicle types using electricity from the grid and fuel cells. The model also
incorporates additional fuel types, such as biofuels (when they differ from standard fossil fuel
technologies), LPG, LNG, hydrogen and e-fuels. In addition, representation of infrastructure for
refuelling and recharging are among the model refinements, influencing fuel choices. A major model
enhancement concerns the inclusion of heterogeneity in the distance of stylised trips; the model considers
that the trip distances follow a distribution function with different distances and frequencies. The
inclusion of heterogeneity was found to be of significant influence in the choice of vehicle-fuels
especially for vehicles-fuels with range limitations.
111
Source: https://ec.europa.eu/transport/facts-fundings/statistics_en
73
ASTRA consists of different modules, each related to one specific aspect such as the
economy, transport demand or the vehicle fleet. The main modules cover the following
aspects:
 Population and social structure (age cohorts and income groups)
 Economy (e.g. GDP, input-output tables, employment, consumption and investment
both at aggregate and at sectoral level)
 Foreign trade (inside EU and to partners from outside EU)
 Transport (including demand estimation, modal split, transport cost and infrastructure
networks)
 Vehicle fleet (passenger and freight road vehicles by segment and drivetrain)
 Environment (including air pollutant emissions, CO2 emissions, energy consumption).
The economy module simulates the main economic variables. Some of these variables (e.g.
GDP) are transferred to the transport generation module, which uses the input to generate
a distributed transport demand. In the transport module, demand is split by mode of
transport. The traffic performance by mode is associated with the composition of the fleet
(computed in the vehicle fleet module) and the emissions factors (defined in the
environmental module), in order to estimate total emissions.
Several feedback effects take place in the ASTRA model. For instance, the economy
module provides the level of income to the fleet module, in order to estimate vehicle
purchase. The economy module then receives information on the total number of
purchased vehicles from the fleet module to account for this item of transport consumption
and investment. Furthermore, changes in the economic system immediately feed into
changes of the transport behaviour and alter origins, destinations and volumes of European
transport flows.
The indicators that ASTRA can produce cover a wide range of impacts; in particular
transport system operation, economic, environmental and social indicators. The
environment module uses input from the transport module (in terms of vehicle-kilometres-
travelled per mode and geographical context) and from the vehicle fleet module (in terms
of the technical composition of vehicle fleets), in order to compute fuel consumption,
greenhouse gas emissions and air pollutant emissions from transport. ASTRA also
estimates the upstream emissions (well-to-tank) due to fuel production and vehicles
production. Therefore, well-to-wheel emissions can be provided as well.
Strategic assessment capabilities in ASTRA cover a wide range of transport measures and
investments with flexible timing and levels of implementation.
Geographically, ASTRA covers all EU Member States plus United Kingdom, Norway and
Switzerland. The model is built in Vensim software and is developed and maintained by
TRT, M-Five and ISI Fraunhofer.
74
Data inputs
ASTRA is calibrated on the EUROSTAT database and data from the Statistical
Pocketbook "EU transport in figures112
. In the context of this exercise, ASTRA model is
calibrated on historical data for 2000-2015.
TRUST model
TRUST is a European scale transport network model developed and maintained by TRT
and simulating road, rail, inland waterways and maritime transport activity. TRUST covers
the whole Europe and its neighbouring countries and it allows for the assignment of
passenger and freight origin-destination (OD) matrices at NUTS3 level of detail (about
1600 zones) on the multimodal transport network113
.
Road rail, inland waterways and maritime transport modes are covered in separate
modules, each with its own matrices that are then assigned simultaneously on the
multimodal transport network.
TRUST is built in PTV-VISUM software environment. The assignment algorithm used is
Equilibrium Assignment which distributes demand for each origin/destination pair among
available alternative routes, according to Wardrop first principle. This principle assumes
that each traveller is identical, non-cooperative and rational in selecting the shortest route,
and knows the exact travel time he/she will encounter. If all travellers select routes
according to this principle the road network will be at equilibrium, such that no one can
reduce their travel times by unilaterally choosing another route of the same OD pair. This
principle has been extended to consider generalised travel cost instead of travel time, where
generalised travel cost can include the monetary cost of in-vehicle travel time, tolls,
parking charges and fuel consumption costs. The impedance function is defined in terms
of generalised time from an origin O to a destination D. Travel costs are defined separately
by link types using combinations of fixed, time-dependent and distance-dependent
parameters. Travel time is estimated endogenously by the model as result of the
assignment. Speed-flow functions are used to model the impact of traffic on free-flow
speeds, given links capacity. The model iterates until a pre-defined convergence criterion
for equilibrium is reached.
TRUST can be used in the context of impact assessments and for supporting policy
formulation and evaluation. It is particularly suitable for modelling road charging schemes
for cars and heavy goods vehicles as well as policies in the field of infrastructure.
Data inputs
The main data sources for inputs to the TRUST model are the EUROSTAT database and
the Statistical Pocketbook "EU transport in figures114
, TENtec Information system115
and
ETISplus database.
112
Source: https://ec.europa.eu/transport/facts-fundings/statistics_en
113
Further information on TRUST is available on http://www.trt.it/en/tools/trust/
114
Source: https://ec.europa.eu/transport/facts-fundings/statistics_en
115
https://ec.europa.eu/transport/themes/infrastructure-ten-t-connecting-europe/tentec-information-
system_en
75
ITS deployment
For assessing the level of ITS deployment an excel tool has been developed, which implies
several steps. First, ITS service types have been grouped into a series of service bundles
to which common deployment assumptions for the baseline and each policy option are
applied. The process for developing the service bundles was informed by the extensive
literature review and consultation with stakeholders.
Table 32: ITS service bundles
Service bundle ITS Services types Rationale Service end-
users
Bundle 1a:
Information and
booking services
for travellers
 Multimodal travel information service
(including linking between modes)
 Multimodal travel information and
booking/re-selling service (MaaS)
ITS services focused on
providing dynamic travel
information and booking
services to support journeys
carried out by travellers.
Active modes,
micro mobility,
public transport,
car users, taxis
Bundle 1b:
Information and
booking services
for drivers
 Travel information service / Road traffic
information & navigation services
 Real-time traffic information service
 Parking (and pricing) information
 Re-charging/re-fuelling location and
pricing information
ITS services focused on
providing dynamic travel
information and booking
services to support journeys
carried out by drivers.
Delivered via smartphone
and/or in-vehicle systems.
Car users, public
transport, taxis,
trucks
Bundle 2: Travel
management
services
 (Enhanced) Traffic network and
incident management systems
 Mobility management services
ITS services supporting
mobility, network and traffic
management by road operators
and transport authorities.
Car users, trucks,
taxis, public
transport (active
modes)
Bundle 3: Road
safety and
security
(excluding C-
ITS)
 SRTI service
 S&S truck parking location information
and reservation system
 eCall (current scope only)
ITS services (non-C-ITS)
intended to create safety and
security benefits
Car users, trucks,
active modes,
taxis (public
transport)
Bundle 4:
Vehicle-to-
vehicle (V2V) C-
ITS
 V2V C-ITS (e.g. Emergency electronic
brake light & Hazardous location
notification)
Day 1 V2V services, with
strong safety benefits.
Applicable to all road types.
Active modes,
car users, trucks,
taxis
Bundle 5:
Vehicle-to-
Infrastructure
(V2I) C-ITS
 V2I C-ITS (e.g. Shockwave damping,
In-vehicle speed limits & Weather
conditions, GLOSA & Signal violation)
Day 1 V2I services that deliver
a range of benefits, with a
particular focus on traffic
efficiency.
Car users, public
transport, trucks,
active modes,
taxis
Bundle 6: Future
C-ITS services
 C-ITS cooperative perception services
(day 2) and automation support services
(day 3) –
Longer term C-ITS services
(2030+).
Car users, trucks,
taxis, public
transport etc.
Note: Bundles 4 and 5 consider a hybrid communication approach.
In a second step, differences between Member States are assessed by considering a
country grouping. Member States are grouped into three categories: ‘Front Runner’,
‘Planned Adopter’, or ‘Follower’, which are based on their technology and institutional
levels of ITS deployment. Several indicators have been used to develop an overall ranking
for each Member State:
 Involvement in ITS deployment projects. This is based on the count of project
involvement for each Member State, normalised by country population size and ranked
(where 1 is greatest project involvement. A list of C-ITS projects was collected as part
76
of past studies116,117
and expanded to include ITS projects in the context of the impact
assessment support study.
 National Access Point (NAP) status. This is based on an analysis of EU EIP A2
Annual NAP Report 2019 and latest list of NAPs (14th January 2021) providing the
status of NAPs for S&S truck parking, SRTI, RTTI, and MMTIS. Scores were assigned
to each country depending on the level of deployment. The status of deployment of
datasets for NAPs were ordered from highest (e.g. operational) to lowest (e.g. no
information or not operational) and scores allocated respectively. Scores were then
combined for each type of NAP (i.e. SRTI and RTTI) and a final ranking was calculated,
where 1 stands for the most advanced NAP status.
 Level 2 and 3 ITS deployment. Based on the analysis provided by the CEDR TEN-T
2019 Performance Report on the distribution of ITS levels for each Member State, an
assessment of Level 2118
and 3119
ITS deployment has been undertaken. The combined
deployment level has then been ranked, where 1 stands for the highest proportion of
ITS deployment of Levels 2 & 3.
 C-ITS hybrid ITS station deployment. The share of TEN-T corridor/core network
equipped with C-ITS hybrid infrastructure has been derived from a comprehensive
analysis of existing and forthcoming C-ITS deployment projects across Europe and
building on the dataset developed in the context of previous studies120,121
. A ranking of
1 stands for greater levels of road network coverage.
The table below presents the ranking for each of the indicators, including the total score
and the assigned country grouping. A lower score denotes more advanced levels of
deployment. The cut-off points between the groupings have been selected based on both
step changes in scores and comparisons with other studies. They have also been validated
by stakeholder feedback.
Table 33: ITS assessment indicators and country groupings
Country
ITS
projects
NAP
Status
ITS L2 & L3
deployment
C-ITS
deployment
Total
score
Grouping
France 13 3 2 2 20 Front Runner
Netherlands 4 10 2 4 20 Front Runner
Slovenia 3 10 5 6 24 Front Runner
Finland 2 6 10 9 27 Front Runner
Czech Republic 9 10 5 5 29 Front Runner
Austria 8 3 17 3 31 Front Runner
Germany 16 3 6 8 33 Front Runner
Sweden 5 10 12 7 34 Front Runner
Belgium 15 16 4 1 36 Planned Adopter
Denmark 6 10 14 11 41 Planned Adopter
Spain 10 10 9 15 44 Planned Adopter
116
Ricardo et al. (2016), Study on the Deployment of C-ITS in Europe: Final Report.
117
Ricardo et al. (2019), Support study for Impact Assessment of C-ITS.
118
Traffic information system (road administration passively manages the network e.g. information about
traffic/weather conditions is provided to road users).
119
Traffic management system (road administration actively manages)
120
Ricardo et al. (2016), Study on the Deployment of C-ITS in Europe: Final Report.
121
Ricardo et al. (2019), Support study for Impact Assessment of C-ITS.
77
Country
ITS
projects
NAP
Status
ITS L2 & L3
deployment
C-ITS
deployment
Total
score
Grouping
Luxembourg 1 3 20 24 48 Planned Adopter
Italy 18 3 19 14 54 Planned Adopter
Portugal 11 25 10 10 56 Planned Adopter
Greece 7 17 17 17 58 Planned Adopter
Hungary 26 10 15 12 63 Planned Adopter
Estonia 26 14 13 24 78 Follower
Croatia 12 19 24 24 79 Follower
Lithuania 26 19 11 24 80 Follower
Poland 21 19 16 24 80 Follower
Ireland 26 14 18 24 83 Follower
Malta 26 26 7 24 83 Follower
Romania 17 23 24 24 88 Follower
Bulgaria 19 21 24 24 89 Follower
Cyprus 26 21 24 24 96 Follower
Latvia 26 24 24 24 98 Follower
Slovak Republic 26 26 24 24 100 Follower
Source: Ricardo et al. (2021), Impact Assessment support study
In the third step, the ITS deployment rates are estimated. The aggregate impact of policy
measures in each policy option on the ITS deployment is estimated in this step. This also
takes into account the deployment dependencies of each service. In addition to deployment
dependencies, other factors considered include: the type of service (i.e. C-ITS), whether
they are mature services or not, and their primary targeted geographic deployment areas
(motorways, urban).
Figure 18 Graphic explaining how ITS services usage is estimated in the modelling
The deployment level takes into account both the availability of the ITS service (driven by
data availability/accessibility) and the uptake by the end-user. The projections for the ITS
and C-ITS data network coverage are combined with a service conversion factor to
estimate the extent of roads along which ITS services are available. Different infrastructure
uptake rates are considered for different road types and between country groupings. Data
78
on the total road network length by road type from the TRUST model road network for the
EU27 has been used to this end.
The uptake by the end-user considers the use of smartphones by drivers or travellers and/or
the penetration of in-vehicle systems into new vehicles. The use of smartphones by drivers
can cover service penetration into both new and existing vehicle fleet for Bundles 1b to 3,
but services are assumed to only be deployed into new vehicles via in-vehicle systems for
Bundles 4, 5 and 6122
. These values are combined with an end-user uptake limit to reflect
that not all travellers and drivers who could use an ITS service will actually use it. In the
OPC, citizens were asked about the reasons for not using ITS services. The majority (42
of 75 responses) stated that they do not know which systems are available for each
situation, while just under half (31 of 75 responses) noted they have concerns about privacy
and re-use of personal data. Other challenges identified include limited added value, ease
of use/access, and concerns about the security of the system. Different uptake rates for
passenger cars, heavy goods vehicles and buses are considered, based on differences in
decision making on whether to use a service. User uptake rates between country groupings
are assumed to be the same.
In the fourth step, the ITS deployment scenarios are combined with the primary impact
data for different ITS services to calculate the percentage improvements over time. The
primary impact data for different ITS services covers:
 The reduction in fuel consumption;
 The reduction in air pollution emissions;
 The reduction in the accident rates;
 The reduction in travel time.
The assumptions on primary impact and cost data are provided in section 5 of Annex 4.
In the final step, the percentage improvements over time are used in the ASTRA and
TRUST modelling framework to derive the impacts of the policy options.
The services in Bundle 1a (Information and booking services for travellers) are treated
slightly differently to the other bundles as the impacts are realised at the individual traveller
level, rather than at a vehicle level. For this bundle, impacts on travel time and cost are
provided separately, although these impacts are combined with the impacts from other
bundles in the ASTRA and TRUST models.
As explained above, since a number of ITS service types have similar functionality,
multiple services are likely to overlap and be applicable to the same driving situations. The
approach for accounting for the overlaps between services, in order to avoid double-
counting impacts, is described in section 6 of Annex 4.
122
Penetration rates of ITS services are applied on new or existing vehicles by vehicle age.
79
2. BASELINE SCENARIO
In order to reflect the fundamental socio-economic, technological and policy
developments, the Commission prepares periodically an EU Reference Scenario on
energy, transport and GHG emissions. The socio-economic and technological
developments used for developing the baseline scenario for this impact assessment build
on the latest “EU Reference 2020 scenario” (REF2020)123
. The same assumptions have
been used in the MIX scenario underpinning the impact assessments accompanying the
‘Fit for 55’ package.
Main assumptions of the Baseline scenario
The main assumptions related to economic development, international energy prices and
technologies are described below.
Economic assumptions
The modelling work is based on socio-economic assumptions describing the expected
evolution of the European society. Long-term projections on population dynamics and
economic activity form part of the input to the model and are used to estimate transport
activity.
Table 34: Projected population and GDP growth per Member State
Population GDP growth
2020 2025 2030 2020-‘25 2026-‘30
EU27 447.7 449.3 449.1 0.9% 1.1%
Austria 8.90 9.03 9.15 0.9% 1.2%
Belgium 11.51 11.66 11.76 0.8% 0.8%
Bulgaria 6.95 6.69 6.45 0.7% 1.3%
Croatia 4.06 3.94 3.83 0.2% 0.6%
Cyprus 0.89 0.93 0.96 0.7% 1.7%
Czechia 10.69 10.79 10.76 1.6% 2.0%
Denmark 5.81 5.88 5.96 2.0% 1.7%
Estonia 1.33 1.32 1.31 2.2% 2.6%
Finland 5.53 5.54 5.52 0.6% 1.2%
France 67.20 68.04 68.75 0.7% 1.0%
Germany 83.14 83.48 83.45 0.8% 0.7%
Greece 10.70 10.51 10.30 0.7% 0.6%
Hungary 9.77 9.70 9.62 1.8% 2.6%
Ireland 4.97 5.27 5.50 2.0% 1.7%
Italy 60.29 60.09 59.94 0.3% 0.3%
Latvia 1.91 1.82 1.71 1.4% 1.9%
Lithuania 2.79 2.71 2.58 1.7% 1.5%
Luxembourg 0.63 0.66 0.69 1.7% 2.0%
Malta 0.51 0.56 0.59 2.7% 4.1%
Netherlands 17.40 17.75 17.97 0.7% 0.7%
Poland 37.94 37.57 37.02 2.1% 2.4%
Portugal 10.29 10.22 10.09 0.8% 0.8%
Romania 19.28 18.51 17.81 2.7% 3.0%
Slovakia 5.46 5.47 5.44 1.1% 1.7%
Slovenia 2.10 2.11 2.11 2.1% 2.4%
Spain 47.32 48.31 48.75 0.9% 1.6%
Sweden 10.32 10.75 11.10 1.4% 2.2%
123
https://ec.europa.eu/energy/data-analysis/energy-modelling/eu-reference-scenario-2020_en
80
Population projections from Eurostat124
are used to estimate the evolution of the European
population, which is expected to change little in total number in the coming decades. The
GDP growth projections are from the Ageing Report 2021 by the Directorate General for
Economic and Financial Affairs, which are based on the same population growth
assumptions. 125
Beyond the update of the population and growth assumptions, an update of the projections
on the sectoral composition of GDP was also carried out using the GEM-E3 computable
general equilibrium model. These projections take into account the potential medium- to
long-term impacts of the COVID-19 crisis on the structure of the economy, even though
there are inherent uncertainties related to its eventual impacts. Overall, conservative
assumptions were made regarding the medium-term impacts of the pandemic on the re-
localisation of global value chains, teleworking and teleconferencing and global tourism.
International energy prices assumptions
Alongside socio-economic projections, transport modelling requires projections of
international fuel prices. The 2020 values are estimated from information available by mid-
2020. The projections of the POLES-JRC model – elaborated by the Joint Research Centre
and derived from the Global Energy and Climate Outlook (GECO126
) – are used to obtain
long-term estimates of the international fuel prices.
The COVID crisis has had a major impact on international fuel prices127
. The lost demand
cause an oversupply leading to decreasing prices. The effect on prices compared to pre-
COVID estimates is expected to be still felt up to 2030. Actual development will depend
on the recovery of global oil demand as well as supply side policies128
.
The table below shows the international fuel prices assumptions of the baseline and policy
options of this impact assessment.
Table 35: International fuel prices assumptions
Source: Derived from JRC, POLES-JRC model, Global Energy and Climate Outlook (GECO)
Technology assumptions
124
EUROPOP2019 population projections: https://ec.europa.eu/eurostat/web/population-demography-
migration-projections/population-projections-data
125
The 2021 Ageing Report : Underlying assumptions and projection methodologies
https://ec.europa.eu/info/publications/2021-ageing-report-underlying-assumptions-and-projection-
methodologies_en
126
https://ec.europa.eu/jrc/en/geco
127
IEA, Global Energy Review 2020, June 2020
128
IEA, Oil Market Report, June 2020 and US EIA, July 2020.
in $'15 per boe 2000 ‘05 ‘10 ‘15 ‘20 ‘25 ‘30 ‘35 ‘40 ‘45 ‘50
Oil 38.4 65.4 86.7 52.3 39.8 59.9 80.1 90.4 97.4 105.6 117.9
Gas (NCV) 26.5 35.8 45.8 43.7 20.1 30.5 40.9 44.9 52.6 57.0 57.8
in €'15 per boe 2000 2005 ‘10 ‘15 ‘20 ‘25 ‘30 ‘35 ‘40 ‘45 ‘50
Oil 34.6 58.9 78.2 47.2 35.8 54.0 72.2 81.5 87.8 95.2 106.3
Gas (NCV) 23.4 31.7 40.6 38.7 17.8 27.0 36.2 39.7 46.6 50.5 51.2
81
Modelling scenarios is highly dependent on the assumptions on the development of
technologies - both in terms of performance and costs. For the purpose of the impact
assessments related to the “Climate Target Plan” and the “Fit for 55” policy package, these
assumptions have been updated based on a rigorous literature review carried out by
external consultants in collaboration with the JRC129
.
Continuing the approach adopted in the long-term strategy in 2018, the Commission
consulted on the technology assumption with stakeholders in 2019. In particular, the
technology database of the PRIMES-TREMOVE model (together with PRIMES, GAINS,
GLOBIOM, and CAPRI) benefited from a dedicated consultation workshop held on 11th
November 2019. EU Member States representatives also had the opportunity to comment
on the costs elements during a workshop held on 25th
November 2019. The updated
technology assumptions are published together with the EU Reference Scenario 2020. The
same assumptions have been used in the context of this impact assessment.
Policies in the Baseline scenario
The policies included in the Baseline scenario build on the MIX scenario framework
underpinning the impact assessments accompanying the ‘Fit for 55’ package, relying on a
combined approach of carbon pricing instruments and regulatory-based measures to
deliver on the ambition of at least 55% emissions reductions by 2030 and climate neutrality
by 2050.
In the context of this impact assessment, the Baseline scenario excludes the revision of the
TEN-T Regulation and other policy initiatives supported by it (e.g. the forthcoming
revisions of the Intelligent Transport Systems Directive, Rail Freight Corridors Regulation,
Combined Transport Directive)130
.
The Baseline scenario assumes no further EU level intervention beyond the current ITS
Directive. It assumes the continuation of the application of the ITS Directive provisions
and the preparation of standards for the already defined priority areas. It also covers:
 The existing ITS activities such as regional and national deployment projects (e.g. C-
Roads and ITS corridors) which are expected to result in important ITS deployment at
regional level, although with poor coverage of services, low levels of interoperability
and no widespread adoption.
 Industry announcements and identified trends around ITS deployment.
The policy measures reflected in the MIX scenario, relevant for the transport sector, are
summarised below:
- Extension of the EU ETS to the maritime sector, as well as to the road transport and
buildings sectors;
129
JRC118275
130
In the context of the MIX scenario the revision of the TEN-T Regulation, the revision of the Intelligent
Transport Systems Directive, the revision of the Rail Freight Corridors Regulation and of the Combined
Transport Directive were represented in a stylised way, ahead of the adoption of the specific legislative
proposals.
82
- Revision of the Renewable Energy Directive;
- ReFuelEU aviation and FuelEU maritime initiatives;
- Revision of the Directive on alternative fuels infrastructure;
- Gradual internalisation of external costs (“smart” pricing);
- Incentives to improve the performance of air navigation service providers in terms of
efficiency and to improve the utilisation of air traffic management capacity;
- Further actions on clean airports and ports to drive reductions in energy use and
emissions;
- Measures to reduce emissions and air pollution in urban areas;
- Pricing measures such as in relation to energy taxation and infrastructure charging;
- Revision of roadworthiness checks;
- Other measures incentivising behavioural change;
- Medium intensification of the CO2 emission standards for cars, vans, trucks and buses
(as of 2030), supported by large scale roll-out of recharging and refuelling
infrastructure. This corresponds to a reduction in 2030 compared to the 2021 target of
around 50% for cars and around 40% for vans.
These policies come in addition to other EU level policies and the National Climate and
Energy Plans, included in the Reference scenario 2020 and also reflected in the MIX
scenario. The full list of policies included in the Reference scenario 2020 is provided in
the Reference scenario publication.
Baseline scenario results
EU transport activity would continue to grow in the Baseline scenario by 2030 and by
2050, albeit at a slower pace than in the past. This is despite the significant impact of
COVID pandemic on transport activity. Freight transport activity for inland modes
(expressed in tonne-kilometres) would increase by 30% between 2015 and 2030 (1.8% per
year) and 55% for 2015-2050 (1.3% per year). Passenger traffic (expressed in passenger-
kilometres) growth would be lower than for freight with a 15% increase by 2030 (1% per
year) and 33% by 2050 (0.8% per year). The annual growth rates by mode, for passenger
and freight transport, are provided in Figure 19.
83
Figure 19: Passenger and freight transport activity in the Baseline scenario (average growth rate per
year)
Source: Baseline scenario, PRIMES-TREMOVE transport model (E3Modelling)
Note: For aviation, domestic and international intra-EU activity is reported, to maintain the comparability with reported
statistics.
Road transport would maintain its dominant role within the EU. The share of road transport
in inland freight would remain relatively stable by 2030 and slightly decrease by 2
percentage points by 2050. For passenger transport, road modal share is projected to
decrease by 2 percentage points between 2015 and 2030 and by additional 2 percentage
points by 2050. Passenger cars would still contribute 71% of passenger traffic by 2030 and
more than two thirds by 2050, despite growing at lower pace relative to other modes.
Rail transport activity is projected to grow significantly faster than for road, driven in
particular by the assumed completion of the TEN-T core network by 2030 and of the
comprehensive network by 2050, supported by the CEF, Cohesion Fund and ERDF
funding, but also by the measures of the ‘Fit for 55’ package that increase the
competitiveness of rail relative to road transport and air transport. Passenger rail activity
is projected to go up by 24% by 2030 relative to 2015 (62% for 2015-2050). High speed
rail activity would grow by 68% by 2030 relative to 2015 (155% by 2050), missing
however to deliver on the milestone of the Sustainable and Smart Mobility Strategy of
doubling the traffic by 2030 and tripling it by 2050. Freight rail traffic would increase by
41% by 2030 relative to 2015 (91% for 2015-2050) also missing to deliver on the milestone
of the Sustainable and Smart Mobility Strategy of increasing the traffic by 50% by 2030
and doubling it by 2050.
Domestic and international intra-EU air transport would grow significantly (by 39% during
2015-2030 and 82% by 2050) following the recovery from the COVID-19 pandemics,
although at lower pace than projected in the past. The lower growth is also driven by the
measures of the ‘Fit for 55’ package.
Transport activity of inland waterways and national maritime also benefits from the
completion of the TEN-T core and comprehensive network and would grow by 19% during
2015-2030 and by 33% by 2050. When considering all short sea shipping, waterborne
transport activity (inland waterways and short sea shipping) would grow by 19% by 2030
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
Total
passeger
transport
Road Rail Intra-EU
aviation
IWW and
national
maritime
Annual
growth
rates
in
Baseline
'95-'15
'15-'30
'30-'50
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
Total freight
transport
Road Rail IWW and
national
maritime
Annual
growth
rates
in
Baseline
'95-'15
'15-'30
'30-'50
84
and 44% by 2050 missing however to deliver on the milestone of the Sustainable and Smart
Mobility Strategy of increasing activity by 25% by 2030 and by 50% by 2050.
Total energy use in transport, including international aviation and international
maritime, is projected to decrease by 9% between 2015 and 2030 and by 42% by 2050,
which in the context of growing activity shows the projected progress in terms of energy
efficiency driven also by the measures of the ‘Fit for 55’ package. These developments are
mainly driven by the CO2 emission performance standards for new light duty and heavy
duty vehicles, supported by the roll-out of recharging and refuelling infrastructure and also
by the shift towards more energy efficient modes such as rail and waterborne transport.
Alternative fuels131
, including renewable and low carbon fuels, are projected to represent
over 15% of transport energy demand (including international aviation and maritime
transport) in the Baseline scenario by 2030 and around 89% by 2050.
Electricity use in transport would steadily increase over time as a result of uptake of zero
and low-emission powertrains in road transport and further electrification of rail. Its share
in the total energy use in transport would go up from around 1.2% in 2015 to close to 4%
in 2030 and 25% in 2050. The uptake of hydrogen would be facilitated by the uptake of
fuel-cell powertrains in road transport and the FuelEU initiative for the maritime transport,
supported by the increased availability of refuelling infrastructure, and is projected to
represent slightly over 18% of energy use in transport by 2050. Around 8% of all transport
fuels in 2030 would be of biological origin, going up to close to 27% by 2050. Finally,
hydrogen-based fuels (e-liquids, e-gas, methanol and ammonia) would provide another
18% for the transport fuel mix by 2050.
131
According to the Directive 2014/94/EU, ‘alternative fuels’ refer to fuels or power
sources which serve, at least partly, as a substitute for fossil oil sources in the energy
supply to transport and which have the potential to contribute to its decarbonisation
and enhance the environmental performance of the transport sector. They include,
inter alia: electricity, hydrogen, biofuels, synthetic and paraffinic fuels, natural gas,
including biomethane, in gaseous form (compressed natural gas (CNG)) and liquefied
form (liquefied natural gas (LNG)), and liquefied petroleum gas (LPG).
85
Figure 20: Share of alternative fuels used in transport (including international aviation and maritime) in
the Baseline scenario
Source: Baseline scenario, PRIMES-TREMOVE transport model (E3Modelling)
CO2 emissions from transport including international aviation but excluding
international maritime, are projected to be 19% lower by 2030 compared to 2015, and 94%
lower by 2050.
Figure 21: CO2 emissions from transport (including international aviation but excluding international
maritime) in the Baseline scenario
Source: Baseline scenario, PRIMES-TREMOVE transport model (E3Modelling)
Compared to 1990, this translates into 1% emission reductions by 2030 and around 90%
by 2050. When accounting the intra-EU aviation and intra-EU maritime in the transport
emissions, the Baseline projections show reductions of 21% by 2030 and 97% by 2050
relative to 2015. When all intra-EU and extra-EU aviation and maritime emissions are
accounted in the transport emissions, the Baseline scenario results in 17% decrease in
transport emissions by 2030 and 93% decrease by 2050 compared to 2015 levels.
NOx emissions are projected to go down by 56% between 2015 and 2030 (87% by 2050),
mainly driven by the electrification of the road transport and in particular of the light duty
vehicles segment. The decline in particulate matter (PM2.5) would be slightly lower by
2030 at 52% relative to 2015 (91% by 2050).
As explained above, the Baseline scenario in the ASTRA and TRUST models are calibrated to the
results of the PRIMES-TREMOVE model.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Baseline Baseline
2015 2030 2050
%
alternative
fuels
in
transport methanol
ammonia
e-gas
e-liquids
liquid biofuel
natural gas
biomethane
hydrogen
electricity
0
100
200
300
400
500
600
700
800
900
1,000
Baseline Baseline
2015 2030 2050
Mt
of
CO2
inland waterways and
national maritime
aviation
rail
other road transport
heavy goods vehicles
vans
cars
86
ITS deployment in the Baseline scenario
As explained above, the ITS deployment is estimated from projections on service
availability and end-user uptake. The level of service availability (expressed as portion of
road network covered) is calculated applying a service conversion factor 132
to the
estimated availability of relevant datasets along the road network.
The uptake of services by users is then considered, which accounts for the ability of users
to access services (i.e. smartphone ownership) and a user uptake factor that recognises
other aspects causing travellers and drivers to not use ITS services. These may include
concerns over data privacy, service applicability, or even an awareness that the service
exists or acknowledgement of the benefits of using specific ITS services.
Service availability
The availability of the services for each ITS service bundle is estimated from the data
coverage and a service conversion factor. Depending on the ITS service bundle a range of
sources has been used to capture the level of network coverage while the relevant
conversion factors have been determined in consultation with stakeholders. The relevant
information for each bundle is provided below:
 For Bundle 1b covering information and booking services for drivers, the data coverage
estimations for RTTI data sets are used133
. In 2021, data coverage for Front Runner
countries is estimated at 72% for TEN-T roads, 47-52% across other motorways and
urban roads, and significantly lower for other inter-urban roads (16%). Coverage is
estimated to be lower for the other two country groupings.
 For Bundle 1a (information and booking services for travellers), Bundle 2 (Travel
management services) and Bundle 3 (Road safety and security applications), data
coverage is based on the RTTI data and adjusted according to the respective statuses of
MMTIS and SRTI dataset availability in NAPs across EU27 as reported in the EU EIP
A2 Annual NAP Report134
and latest list of NAPs (14th
January 2021)135
.
- Bundle 1a: In 2021, data coverage for Front Runner countries is estimated at 66%
for TEN-T and urban roads, 48% across other motorways and 12% for other inter-
urban roads.
- Bundle 2: In 2021, data coverage for Front Runner countries is estimated at 44% for
TEN-T roads, 30-31% across other motorways and urban roads, and 7% for other
inter-urban roads.
132
The probability that the availability of data lead to development of services utilizing them.
133
VVA et al. (2020), Supporting study on activities 3.2, 3.3 and 3.4 of the new working programme of the
ITS Directive.
134
EU EIP, 2019. EU EIP A2 Annual NAP Report
135
https://ec.europa.eu/transport/sites/default/files/its-national-access-points.pdf
87
- Bundle 3: In 2021, data coverage for Front Runner countries is estimated at 75% for
TEN-T roads, 55% across other motorways and urban roads, and 14% for other inter-
urban roads.
 For Bundle 4 (vehicle-to-vehicle C-ITS services), the availability of services is
assumed to be linked to the deployment of in-vehicle systems, which is covered in the
end-user uptake assumption layer.
 For Bundle 5 (vehicle-to-infrastructure C-ITS services), data coverage across the road
network is estimated from a review of existing C-ITS deployment activities and the
portion of TEN-T road network along which infrastructure supporting hybrid C-ITS has
been deployed. In 2021, network coverage for Front Runner countries is estimated at
19% for TEN-T roads, 3% for urban roads and 0% for other inter-urban roads. Coverage
is estimated to be lower for the other two country groupings.
An annual increase in data coverage of 2% for Bundle 1a-3 is assumed under the
baseline136
, while for Bundle 5, the rate of deployment estimated between 2015 and 2020
is projected until 2023 and then assumed to be constant (25% for TEN-T roads in Front
Runner countries), in line with the end date of most current deployment projects. To date,
deployment of C-ITS services has been relatively slow and fragmented across the EU
owing largely to the large investment costs required and the uncertainty due to a lack of
coordinated infrastructure and vehicle deployments. In absence of further EU level
intervention, it is projected that the progress on infrastructure deployment, data generation
and sharing and stakeholder coordination will stall, although maintenance of existing units
is assumed.
A service conversion factor of 0.7 is assumed for Bundles 1a, 1b and 3, while for Bundle
2, a higher factor of 0.9 is assumed due to the closer alignment between the data collection
and service provision by stakeholders. The service conversion factors were presented and
validated with stakeholders during the 3rd
workshop that took place on 19th
January 2021.
Figure 22 below shows the expected development of service availability in the baseline for
Bundles 1 to 3, on the basis of the data availabilities and a 0.7 service conversion factor.
It represents service availability along TEN-T roads, which are assessed to display the
highest levels of deployment across all road type. In Bundle 1a, service availability in
urban roads is estimated to be equal to TEN-T roads while in the other bundles, service
availability reduces across other motorways and interurban roads. The figure represents
service availability in Front Runner countries only. The level of coverage is estimated to
be 10% lower for Planned Adopters and 20% lower for Followers.
136
VVA et al. (2020), Supporting study on activities 3.2, 3.3 and 3.4 of the new working programme of the
ITS Directive.
88
Figure 22: Baseline service availability across TEN-T roads in Front Runner countries
Source: Ricardo et al. (2021), Impact Assessment support study
End-user uptake
The end user uptake of each service bundle determines the conversion of service
availability to final service usage. This is estimated on the basis of the level of in-vehicle
system deployment and/or smartphone ownership (depending on the bundle) and an end
user uptake factor. A combination of sources has been used to estimate the evolution of
smartphone ownership among the travellers and drivers who could use ITS services137, 138,
139, 140
.
As shown in Figure 23 a sharp increase in smartphone ownership is expected until 2025
followed by a levelling off in the following years and a maximum value of roughly 97%
by 2040.
137
Anderson, M. P. A., 2017. Technology use among seniors. [Online]
Available at: http://www.pewinternet.org/2017/05/17/technology-use-among-seniors/
[Accessed 01 05 2021]
138
Ricardo Energy & Environment, 2018. Safety of life study, s.l.: 5GAA.
139
Eurostat, 2020. Being young in Europe today - digital world. [Online]
Available at: https://ec.europa.eu/eurostat/statistics-
explained/index.php?title=Being_young_in_Europe_today_-_digital_world
[Accessed 20 05 2021]
140
Silver, L., 2019. Smartphone Ownership Is Growing Rapidly Around the World, but Not Always
Equally. [Online]
Available at: https://www.pewresearch.org/global/2019/02/05/smartphone-ownership-is-growing-
rapidly-around-the-world-but-not-always-equally/
[Accessed 15 06 2021]
89
Figure 23: Projection of smartphone ownership among potential ITS users
Source: Ricardo et al. (2021), Impact Assessment support study
The capability of passenger cars to support ITS services (excluding C-ITS) is assumed to
be aligned with the cellular connectivity of new vehicles. Available sources indicate this
could go up from 46% in 2018 to 100% by 2022.141,142
Bundle 1a can be supported by smartphones only, Bundles 1b, 2 and 3 can be supported
by smartphones and connected vehicles, while Bundles 4 and 5 can only be supported by
dedicated in-vehicle C-ITS systems.
The assumptions used for estimating the end user uptake are provided below:
 For Bundle 1a (information and booking services for travellers), end-user access
to services is based on the proportion of total travellers with a smartphone.
 For Bundle 1b (information and booking services for drivers) and Bundle 3 (Road
safety and security applications), the maximum value between smartphone and in-
vehicle system projections is used to determine end-user access to ITS services in
new cars. Smartphone ownership is assumed to drive ITS access in the existing
passenger car fleet. Uptake is fixed at 90% for public transport and freight vehicles
reflecting the greater penetration of connected devices in these vehicles and more
rational and commercially minded decision making behind whether to utilise a
service that will bring safety and efficiency benefits.
 For Bundle 2 (Travel management services), uptake by the driver is assumed to be
passive and so user uptake is fixed at 100% across both new and existing vehicles.
 For Bundles 4 and 5, end user uptake is derived from assumptions on deployment
of in-vehicle systems in new vehicles only. In the baseline, deployment in new
vehicles reaches 100% in 3 full model cycles (7 years for passenger cars and 9
years for heavy goods vehicles and buses), starting from 2019. No aftermarket
uptake of C-ITS services (Bundle 4 and 5) is assumed. A study on the feasibility
141
Data Task Force, 2020. Data Task Force - Final report & recommendations
142
Ricardo Energy & Environment, 2018. Safety of life study, s.l.: 5GAA.
90
of retrofitting for Advanced Driver Assistance Systems (ADAS)143
shows very low
retrofit shares in the baseline in the total European fleet (0.2-0.4%). These services
can only be supported by in-vehicle systems and not by smartphones.
 A service uptake cap factor of 0.8 is also applied to end-user uptake in passenger
cars for Bundles 1b and 3. For Bundle 1a, the uptake cap factor is 0.7, reflecting
the lower uptake rate of multimodal service among travellers.
Figure 24 presents the estimated service usage in the baseline for a combination of country
grouping, road and user types, which represent the upper range of service usage. Services
in Bundles 1-3 start from a higher level of usage in 2021 compared to C-ITS services
(Bundles 4-5) that depend on the continued roll out of dedicated infrastructure and
deployment of equipped vehicles, which takes time. For bundle 6 no service usage is
project and for bundle 1a geographical scope is urban roads, rather than TEN-T.
Figure 24: Overall service usage in the baseline of each service bundle – for Front Runner countries across
TEN-T roads
Source: Ricardo et al. (2021), Impact Assessment support study
3. ASSUMPTIONS ON THE ITS DEPLOYMENT IN THE POLICY OPTIONS
This section provides the detailed assumptions on service availability and end user uptake
in the policy options relative to the baseline. The information supporting the data inputs
and assumptions comes from the findings of a literature review, but feedback from
stakeholders as part of surveys, interviews and workshops has also been used to develop,
test validate the assumptions.
Service availability
The tables below present the service availability deployment assumptions for the policy
options, namely the data coverage and the service conversion.
Table 36: Data coverage in the policy options
PO1 PO2 PO3
Link with the measures of the policy options
Increased interoperability of data (where
available) for emerging services due to
standards development in new priority areas
PO1 + Increased availability of
data due to mandates for data
sharing and quality for MMTIS,
RTTI and S&S truck parking
services
PO2 + Improved accessibility of in-
vehicle data due to standard
development
143
VTT, ECORYS, 2020. Study on the feasibility, costs and benefits of retrofitting advanced driver
assistance to improve road safety, s.l.: European Commission
91
(i.e. multimodal services, traffic/mobility
management, CCAM)
No direct impact on data availability
Increased availability of in-vehicle data due
to common access requirements
Impact on deployment
 Bundles 1, 2 – annual coverage increase
rate rises to 2.5%
 Bundle 3 – annual coverage increase rate
rises to 3% post-2025 for TEN-T and post-
2030 for other roads
 Bundle 4 - same as baseline
 Bundle 5 – from 2023, deployment
projected at 25% of deployment rate
between 2015 and 2023
 Bundle 1 – coverage reaches
100% by 2028 for TEN-T
and 2030 for other roads
 Bundle 2 - same as PO1
 Bundle 3 – reaches half of
the gap from PO2 to 100%
by 2030 and other roads
increase annual increase rate
to 3% post-2025
 Bundle 4 - same as baseline
 Bundle 5 – Same as PO1
 Bundle 1 & 2 - same as PO2
 Bundle 3 – coverage reaches 100%
by 2030 for TEN_T and other roads
same as PO2
 Bundle 4 - same as baseline
 Bundle 5 – from 2023, deployment
projected at the same rate as
deployment rate between 2015 and
2023. For other roads project at 50%
the rate of TEN-T.
Table 37: Service conversion in the policy options
PO1 PO2 PO3
Link with the measures of the policy options
Small improvement due to streamlined interaction
with ITS stakeholders
Services deployment unblocked due to
GDPR/ePrivacy alignment and C-ITS Trust model
Improvement in services development as ITS
stakeholders are more involved in implementation.
Small uptake in development of services relying on in-
vehicle data due to improved transparency and
increased support of business due to C-ITS Trust
model
PO1 + Small improvement in
services deployment due to better
data sharing through NAP
coordination institutionalisation
PO2 + Increased
deployment of
services due to
SRTI and Day 1 C-
ITS services
mandate
Impact on deployment
 Bundles 1 & 3 - increase 5 p.p. to 75%
 Bundle 2 - same as Baseline
 Bundle 4 & 5 – enhanced deployment in vehicles
(see user uptake assumptions)
 Bundles 1 & 3 – 100% service
conversion for TEN-T and 90%
for other roads, 2 years after full
coverage of data accessibility.
 Bundle 2 - same as Baseline
 Bundles 1 & 3 -
same logic
applied as in PO2
 Bundle 2 - same
as Baseline
End-user uptake
End-user uptake assumptions determine whether end-users are able to use an available
service, and accounts for a likelihood of whether they would use the service. In the OPC,
the biggest barrier for citizens using ITS services have been identified as being: not
knowing which systems are available in a given a situation, followed by concerns on the
use of personal data and the ease of use of systems. For Bundle 1a, the assumptions cover
uptake by travellers not limited to driving, while for all other bundles, uptake is based on
assumed penetration of ITS services into the vehicles, either via in-vehicle systems or
smartphones. Different uptake rates for passenger cars, heavy goods vehicles and buses
are considered, but the uptake rates between country groupings are assumed to be the same.
Table 38 presents the end-user uptake assumptions for the policy options.
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Table 38: End-user uptake in the policy options
PO1 PO2 PO3
Link with the measures of the policy options
Increase in user uptake due to GDPR,
ePrivacy and passenger rights alignment
Small increase for C-ITS services due to
improved trust (C-ITS trust model)
Further increase use of C-ITS due to C-
ITS trust model institutionalisation
Same as PO1
No direct impact on user uptake -
second order effect as a result of
improved services availability and
effectiveness
Same as PO1
No direct impact on user uptake
- second order effect as a result
of improved services
availability and effectiveness
Impact on deployment
 Bundles 1 & 3 - for cars the user uptake
cap increases +5p.p to 85% in 2025. For
freight/PT, uptake fixed at 90%
 Bundle 2 – Same as baseline
 Bundles 4 & 5 - All new vehicles
equipped in 2 full model vehicle cycles
 Bundles 1 & 3 – for cars, the user
uptake cap increases further
+5p.p. to 90% in 2025. For
freight/PT, uptake fixed at 90%
 Bundle 2 – Same as baseline
 Bundles 4 & 5 - same as PO1
 Bundles 1 & 3 same as PO2
 Bundle 2 – Same as baseline
 Bundles 4 & 5 - all new
vehicles equipped in 2 vehicle
facelift cycles (4 years for
cars and 5 years for
freight/buses)
The usage increase over time of all service bundles in all policy options is presented in the
following three figures:
Figure 25: Figure 8: Service usage of information and booking bundles in front runner countries across
policy options
Figure 26: Service usage of travel management and road safety bundles in front runner countries across
policy options
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Figure 27: Service usage of C-ITS bundles in front runner countries across policy options
4. ASSUMPTIONS ON ITS SERVICE COST DATA
This section provides the assumptions for the ITS technology and service costs, which are
an important component of the cost-benefit analysis. The cost data collected for the 2016
and 2019 C-ITS studies has been used as a starting point and has been reviewed and
expanded for costs related to broader ITS services.
The hardware and associated software and services used to deliver ITS services can be
broadly categorised into:
1. Smartphones, which support the use of most ITS services by individuals in the
transport system. Smartphones can support the deployment of services among
travellers and in new and existing vehicles. The functionality of using smartphones in
vehicles is increasing with many manufacturers offering smartphone integration
technologies such as ‘mirroring’.
2. In-vehicle systems, which are fitted by the vehicle manufacturer and are attached to
the vehicle communication buses to enable cellular and/or direct communications that
support the delivery of C-ITS services to drivers. It is assumed there is no aftermarket
uptake of C-ITS services (Bundle 4 and 5). A study on the feasibility of retrofitting
for Advanced Driver Assistance Systems (ADAS) showed very small shares of
retrofitting in the total European fleet (0.2-0.4%) (DG MOVE, 2020).
3. Roadside ITS infrastructure such as RSUs, VMSs, sensors, cameras, and smart
traffic lights, which generate and collect data to be used for ITS services, facilitate
the delivery of ITS services and enable communications between vehicles and the
road infrastructure supporting V2I C-ITS services.
4. Central ITS systems, which may be part of a centralised traffic management system
and include NAPs. These systems can support ITS services for an entire city, road
operator, or national highway system etc.
For each of them, the following cost categories are considered:
 Upfront costs, i.e. one-off costs incurred at the point of installation/commissioning.
 Ongoing costs, i.e. the recurring costs associated with operating each sub-system.
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 Equipment lifetime, to establish the need to account for replacement costs within the
lifetime of the cost-benefit analysis (2015 to 2040).
 The cost owner, to enable an estimation of the impact of different cost items on the
various key stakeholders in the deployment of C-ITS services.
Building on the cost data available for C-ITS service, the EU EIP evaluation reports on
each of the 5 European funded corridors were reviewed; Arc Atlantique II, Crocodile,
MedTIS, Next ITS, Ursa Major. Cost data was also extracted from the support study on
activities 3.2, 3.3 and 3.4 of the new working programme of the ITS Directive (Tavares,
2020) and the C-MOBILE ex-ante cost-benefit analysis (C-MOBILE, 2018).
Technology Learning Rates
Many systems deployed to support the rollout of ITS services are at a relatively early stage
of maturity and costs are likely to improve over time. To account for this, a learning rate
of 15% is applied to all up-front costs for in-vehicle and roadside ITS sub-systems, where
for every doubling in installed volume, up-front costs reduce by 15%. These learning rates
are based on an analysis of low CO2 technologies performed by the US EPA and NHTSA
(US EPA, NHTSA, 2012) and account for feedback received from experts as part of the
2019 C-ITS study (Ricardo, 2019).
To avoid a strong decrease in costs due to the step increase in units in early years, starting
volumes have been defined for vehicles and RSUs. Only when these starting volumes are
reached, learning rates begin to apply. For vehicles the starting volume is set to 30 million
units. For roadside ITS infrastructure the starting volume is set to 30,000 units. Before the
starting volumes are reached, a uniform 2% annual reduction is assumed (Analysys Mason,
2017).
Smartphones
Smartphones serve as the end-user interface to deliver an ITS service, applicable to several
of the service bundles considered in this impact assessment. Smartphones owned by the
user will require a specific app (developed by the ITS service provider) and cellular
connection in order to use the ITS service in question.
Route navigation services may be delivered through other personal ITS devices, such as
personal navigation devices (PNDs), although current market trends suggest that
smartphones are the principle device used by consumers for such services144
and this
market share is expected to increase even further with the continued development of
applications and the roll-out of 5G. Therefore, in this impact assessment, drawing on the
impact assessment support study, it has been assumed that ITS services on personal devices
will only be delivered though smartphones.
In the future, technically, it is possible that smartphone devices will be able to access
vehicle data and be used to support secure communications for C-ITS services (Bundle 4
and 5) but in this impact assessment it is assumed that C-ITS services can only be delivered
144
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via in-vehicle systems. There are examples today of smartphones supporting similar
services to those offered by C-ITS, but these are classified in Bundle 3 as SRTI services.
Smartphone related costs are considered in Bundles 1A, 1B, 3.
A summary of the upfront and ongoing costs associated with smartphones is included in
the table below. These are discussed in more detail in the following sections including
sources of cost data, applicability to bundles and deployment dependencies.
Table 39: Breakdown of costs for smartphones
Cost item Input Unit Cost owner Relevant bundles
Upfront costs
Equipment €0 Per smartphone End-user 1A, 1B, 3
App cost €0 Per smartphone End-user 1A, 1B, 3
App development €500,000 Per app platform App developer 1A, 1B, 3
Ongoing costs
(per year)
Data €0 Per smartphone End-user 1A, 1B, 3
App subscription €0 Per smartphone End-user 1A, 1B, 3
Software updates 20% capex
(i.e. €100,000)
Per app platform App developer 1A, 1B, 3
Upfront costs
Equipment and app cost
In the cost-benefit analysis for this impact assessment, the upfront costs associated with
end-users are assumed to be zero. That is, the cost for equipment (i.e. smartphone) and the
upfront cost for the app. It is assumed that end-users will already be in possession of a
smartphone, thus it does not represent an additional cost.
Concerning the cost to download ITS apps, a free model has been assumed. In this business
model, an application is developed and maintained by an app developer who bears the cost,
although they may be supported by a public body or OEM. There will be no upfront fee to
download the app and no subscription fees to access the service. The funding body of the
applications may choose to recoup some of its costs through e.g. allowing advertising
within the app.
It should be noted that there are also other business models available, such as a
subscription-based model or app store/online marketplace-based model, in which the latter
would incur an upfront cost. However, analysis of the current market shows that the top
four navigation apps, accounting for 98% of the market, all employ a free model145
. There
is a possibility that as these apps incorporate new features and become more complex, a
cost may be incurred either through a subscription or upfront cost. However, in absence of
such information, it has been assumed that the upfront cost for all smartphone apps will be
zero throughout the time period considered in the assessment.
App development
Upfront app development costs are borne by the app developer, which could be either a
private ITS service provider or a public body such as a road authority. The costs for
developing smartphone apps vary considerably depending on the nature of the app. In this
145
https://themanifest.com/mobile-apps/popularity-google-maps-trends-navigation-apps-2018
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impact assessment, up-front app development costs are assumed to be €500,000 per app in
line with the C-ITS deployment study (Ricardo, 2019). This reflects the upper end of app
development costs reflecting the technical complexity, communications compatibility and
scale that would be required. This value is in line with estimated app development costs
given by COMeSafety 2 and Score@F project as well as general online website
resources146
.
While there may be a number of individual platforms developed initially, it is expected
that these will be merged together in the future, with several operating in multiple Member
States depending on the nature of the service. In this impact assessment, it is assumed that
there will be a maximum of one major app for each Member State (27 in total) and that a
new app will be developed for each relevant service bundle. It is assumed that the number
of service platforms developed scales linearly with the service availability. Thus, for every
3.7% (100%/272) service availability, one app will be required.
Ongoing costs
Concerning end-users, there are two types of ongoing costs associated with ITS
smartphone services, both of which have been assumed to be zero in this assessment:
 Subscription fees: As discussed above, no annual subscription fees is assumed for the
use of the ITS smartphone application, as all services are assumed to be provided for
free by road authorities and private service providers. It is recognised that some MaaS
platforms have a subscription model however, this fee would typically provide access
to various transport modes and so is not an additional cost (and may actually represent
a cost saving). For users who are regularly using public transport and other services, the
MaaS platform serves as convenience rather than having an impact on the end user cost.
In the absence of reliable information on the costs of MaaS subscriptions and to what
extent they represent a cost or a cost saving, it has been assumed that the subscription
cost will be roughly equal to the traveller costs and thus the same as in the baseline.
 Data: Use of C-ITS applications in smartphones will require the user to transmit and
receive additional data via the cellular network. However, in this assessment it is
assumed that the cost of data will already be included in the end-user’s mobile phone
contract and thus does not represent an additional cost. There is already an increasing
trend for smartphone users to increase their data plans147
, which is expected to be large
enough to cover the data usage for ITS in the majority of cases.
For app developers, ongoing costs are expected for the ongoing operation and maintenance
of their apps, as well as research and development to improve their service and provide
necessary software updates. Other costs include monitoring, engagement and marketing.
These costs combined are assumed to be 20% of the upfront costs, with sources indicating
that 15-20% represents the industry norm148
.
146
https://www.velvetech.com/blog/how-much-mobile-app-cost/
147
https://www.ericsson.com/en/mobility-report/articles/shifting-mobile-data-consumption-data-plans
148
https://www.businessofapps.com/app-developers/research/app-development-cost/
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In-vehicle systems
In-vehicle systems are fitted by the vehicle manufacturers and are attached to the vehicle
communication buses. These can enable both V2V communications and V2I along suitably
equipped roads, as well as acting as the user interface for ITS services. Retrofitted vehicle
ITS sub-systems are not considered and these costs are only relevant for new vehicles.
In the assessment it is assumed that in-vehicle systems support hybrid communications
(both cellular and direct) in line with a technology neutral approach to service delivery.
The same cost is applied to each vehicle type i.e. passenger vehicles, freight vehicles, and
public transport.
A simple business model is assumed in the assessment, whereby costs are only included
for the additional equipment/software required to deliver ITS services in new vehicles.
Additional up-front equipment, installation and software development costs are included
at cost price (i.e. OEM costs), whilst a number of additional ongoing costs are incurred by
both the OEM and end-user.
Some of the costs assumed to be incurred by the OEMs will eventually be passed on to the
consumer through applying a mark-up (for example the NHTSA study assumes a 51%
mark-up between OEM cost and consumer price on all vehicle components (Harding,
2014) and such a cost will often be included in the cost of the new vehicle.
A summary of the upfront and ongoing costs associated with in-vehicle systems is included
in the table below. These are discussed in more detail in the following sections including
sources of cost data, applicability to bundles and deployment dependencies.
Table 40: Breakdown of costs for in-vehicle systems
Cost item Input Unit Cost owner Relevant
bundles
Upfront
costs
Hardware, installation,
integration, and licensing
€288 Per vehicle OEM 4, 5
Software development €500,000 Per model OEM 4, 5
Ongoing
costs
Maintenance 5% of equipment
costs
Per vehicle End-user 4, 5
Secure Communications €2.36 Per vehicle End-user 4, 5
Data / app subscription €0 Per vehicle End-user 4, 5
Software updates €100,000 Per model OEM 4, 5
Upfront costs
Hardware, installation, integration, and licencing
To enable ITS services based on a hybrid communication approach (that supports both
cellular and direct communications), a number of in-vehicle components are required,
including: two transmitter/receivers, two antennas, an electronic control unit, and
additional wiring. Two antennas and transmitter/receivers are assumed to be necessary –
one will be used to send and receive basic safety messages, whereas the other will be
required for the security aspects of V2X communication, such as receiving certificates and
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certificate revocation lists (NHTSA, 2014). The breakdown of costs, expressed in 2015
prices, are provided in the table below and followed by a more detailed description.
Table 41: Breakdown of costs included in hardware, installation, integration and licencing
Cost Value (€)
Transmitter/receiver 160.0
Antenna 12.3
Electronic Control Unit 55.4
Wiring 11.1
On-board cellular equipment 12.3
Installation 8.5
Integration 28.5
Total 288.1
The equipment costs used in this assessment draw on the C-ITS Deployment study. There
are different technologies that support direct communication (e.g. DSRC and PC5), but the
costs are assumed to be similar (Ricardo Energy & Environment, 2020) and no distinction
is made between them. Equipment costs that are not included in the assessment are the in-
vehicle screen GPS costs. Although each of these are necessary to enable the delivery of
an ITS service, 97% of new vehicles are equipped with GPS systems already149
and the
majority of OEMs are already including in-vehicle screens. Thus, in the assessment it is
assumed that all new vehicles have them in place and therefore do not represent an
additional cost.
Installing the additional equipment in vehicles also has implications in terms of labour
costs.
Integration costs include activities such as linking the equipment required to receive and
process the signals for C-ITS services to the rest of the vehicle’s safety and other systems
and carrying out all safety and functionality testing required for certification.
These costs are only applicable to Bundle 4 and Bundle 5. However, given that the
equipment only needs to be installed once to enable C-ITS communication (both V2V and
V2I), the cost applies once per vehicle. The costs outlined above apply to each vehicle
equipped and therefore will scale with vehicle deployment.
Software development costs
Software must be developed to support a range of ITS services, i.e. the software to process
the incoming/outbound signals and to decide what to do with them, before sending further
signals to the vehicle’s CAN bus to request responses from various vehicle systems (e.g.
displays, avoidance manoeuvres, etc.).
The initial software development costs would be approximately €1mn per model, based on
a team of ten engineers working for a year to develop the software (BMW, 2014). Software
could be shared to some extent across different vehicle models, due to significant overlap
between the software deployed to different vehicle models from the same OEM. However,
the differing complexity of different categories of vehicles (e.g. A-category versus E-
149
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category) would mean that individual vehicle models would still incur approximately 50%
of the total development costs described above. Hence, in the assessment the figure of
€500,000 per model has been assumed for each OEM. This figure has been transformed
into a cost per vehicle using the number of vehicles sold and the number of models per
OEM, accounting for a 4-year facelift cycle.
These costs are only applicable to Bundle 4 and Bundle 5. However, given that the same
software will be used for V2V and V2I (excluding minor updates) the cost applies once
per vehicle i.e. the cost is not duplicated for Bundles 4 and 5. The costs outlined above
apply to each vehicle equipped and therefore will scale with vehicle deployment.
Ongoing costs
Ongoing costs for end-users are composed of maintenance, secure communications, data
and application costs and OEM development of in-vehicle software:
 The additional equipment installed to support C-ITS services in new vehicles is likely
to lead to incremental maintenance costs above those that would normally be incurred.
A maintenance cost equal to 5% of the capital cost of ITS equipment per year is assumed
in this assessment. It is assumed that this cost is borne by the vehicle end-user.
 A secure communications management system is necessary for vehicles to provide and
receive secure and trusted communications. The cost of secure communications was
estimated in the C-Mobile report to be €2.36 per vehicle per year (C-MOBILE, 2018).
It is assumed that this cost is borne by the vehicle end-user.
 The cost of data to enable hybrid communications is estimated to be €2.49 in the C-
Mobile report (C-MOBILE, 2018). However, it is unlikely that OEMs will pass this
cost on the end-users as the value is minimal and instead will be included in the upfront
cost of the vehicle.
 In some cases, OEMs may charge a subscription fee for the software or access to new
services. However, no additional software subscription cost has been assumed relative
to the baseline as it will be incorporated into the cost of the vehicle.
 A number of studies point to the potential effect of C-ITS services on insurance costs
(particularly for safety-focused C-ITS services), however due to the lack of data
available to support this assertion, these benefits were not included in the analysis.
Ongoing costs for OEMs are linked to necessary software updates, which are assumed to
be 20% of the upfront costs (i.e. €100,000 per year), which is in line with the software
updates cost required for smartphones.
Roadside ITS Infrastructure
Roadside ITS infrastructure is necessary for generation of data and delivery of services. It
includes equipment such as RSUs, VMSs, sensors, cameras, and smart traffic lights. For
the purposes of this assessment, the costs are divided into two main groups:
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 C-ITS Stations (RSUs) allow V2I communications along specific stretches of roads,
most likely deployed at intersections (relevant to Bundle 5). It is assumed that all
deployment of ITS stations are new units.
 Roadside infrastructure (RSI) encompasses all other infrastructure on the roadside
that is required for the generation and collection of data and delivery of ITS services.
It is assumed that the cost of deploying, running and maintaining roadside ITS
infrastructure is assigned to relevant public authorities. Deployment and upgrades occur to
stretches of road and signalised traffic junctions at a rate determined by service availability
in each policy option. In some cases, existing infrastructure will need to be upgraded to
ensure that services can be delivered, while in other cases RSI will need to be newly
deployed.
Full deployment of C-ITS services is not assumed to require full coverage of RSUs along
the whole road network. A hybrid approach combining direct and cellular communication
is the approach supported by most stakeholders (Ricardo Energy & Environment, 2020),
with RSU deployments focused on hot spot locations where there is high data traffic or a
guaranteed level of performance is required. Intersections are locations where C-ITS use
cases are typically most safety critical with high performance requirements and so the
number of intersections across Europe represents the maximum stock of RSUs with
deployment scaling in line with service availability assumptions.
RSI will be needed throughout the road network to ensure that sensors and cameras
generate relevant data, and VMS can deliver services to users on the road. The type and
scale of RSI varies between bundles and therefore different costs can be expected.
However, for simplicity, it has been assumed that each service bundle requires the same
type and scale of RSI to ensure delivery of the ITS service.
Costs associated with integrating roadside ITS infrastructure with local traffic controllers
are covered in installation costs, while costs associated with integration into central traffic
management centres (TMCs) are dealt with separately in the central ITS sub-system
category.
A summary of the upfront and ongoing costs associated with roadside ITS infrastructure
is included in the table below.
Table 42: Breakdown of costs for roadside ITS infrastructure
Cost item Input Unit Cost owner Relevant bundles
Upfront costs
RSU equipment and installation €14,116 Per RSU Public body 5
RSI equipment and installation €68,104 Per unit Public body 1A, 1B, 2, 3, 4, 5
RSI upgrade €18,151 Per unit Public body 1A, 1B, 2, 3, 4, 5
Ongoing costs
RSU Maintenance 5% of CAPEX Per unit Public body 5
RSI Maintenance 10% of CAPEX Per unit Public body 1A, 1B, 2, 3, 4, 5
Power consumption €18.40 Per unit Public body 1A, 1B, 2, 3, 4, 5
Data €100 Per unit Public body 1A, 1B, 2, 3, 4, 5
Secure Communications €37.91 Per unit Public body 1A, 1B, 2, 3, 4, 5
Upfront costs
RSU equipment and installation
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The costs for ITS station equipment and installation were taken from the C-ITS
deployment study and updated with inputs from literature. The total upfront cost to install
a new RSU capable of delivering C-ITS functionality has been calculated to be €14,116.
A breakdown of the costs in presented in the table below, followed by a more detailed
description.
Table 43: Breakdown of costs included in RSU installation (in 2015 prices)
Cost Value (€)
Equipment/hardware 6,617
Installation 7,500
Total 14,117
This is composed of:
 An equipment/hardware cost: The equipment cost for a new roadside ITS sub-system
with traffic monitoring sensors is estimated to cost €6,001.2, as reported in the C-
Mobile study (C-MOBILE, 2018). This cost is also in line with the C-ITS deployment
study, based on stakeholder’s interviews, and other EU studies such as SAFESPOT
(BASt et al., 2010).
 Installation and mounting costs will vary depending on the complexity of installation.
Research shows that a number of activities are typically required for RSU installation
and that costs will be highly site (and possibly Member State) dependent. A report by
the US DoT (NHTSA, 2014) suggests that in addition to equipment and installation
costs, the following activities must be considered:
o Radio survey per site – to determine optimum placement of the ITS-G5 radio and
antenna for maximum coverage
o Map / GID generation – to accurately map the road layout, especially at
intersections
o Planning – estimated to be 5% of total cost
o Design – costs related to installation of RSUs in each location
o System integration and licence – administration costs associated with the new RSU
o Traffic control – during installation of the unit, including any safety signage
 The C-Mobile report suggests that a simple installation may cost €3,000, whereas a
more complex installation would be in the region of €12,000. An average value of
€7,500 has been assumed, as in the C-ITS deployment study.
These costs are associated only with Bundle 5 (V2I services). To apply and scale these
costs with deployment, an EU stock of 180,000 RSUs is assumed (Wimmershoff, 2011)
(on the basis that RSUs will be deployed at intersections only) and distributed among
Member States based on country groupings. It is assumed that the number of RSUs
deployed scales linearly with the service availability.
RSI Installation and Upgrade
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As described above, RSI encompass all roadside infrastructure excluding RSUs, that
facilitate the delivery of all ITS services by supporting the collection of road data and
bringing all infrastructure into a digital ecosystem. In some cases, the RSI will exist and
need to be upgraded and in other cases new deployment is needed. The costs for RSI were
determined based on EU EIP evaluation reports and cost data from US DoT150
. As noted
above, service bundles will require different type and scale of RSI deployment to facilitate
the delivery of ITS services. This is dependent on several factors, such as nature of the
service, existing infrastructure, location and road type. Given the complexity of RSI
deployment, individual projects have been analysed and average costs per individual piece
of equipment have been used to determine a cost per RSI unit.
The estimated costs for RSI used in this assessment are:
 Installation of a new unit is estimated at €68,105. This includes the cost for equipment
(€60,605) and the installation costs (€7,500), which is assumed to be the same as RSUs.
 Upgrade to existing RSI unit is estimated at €18,151. This figure is estimated to be
25% of new equipment cost (€15,151) and the installation costs are assumed to be
€3,000, equal to a ‘simple’ installation cost of RSUs.
These costs are associated with all bundles but only need to be applied once as the RSI
will jointly facilitate the provision of all services. In the assessment, the following
assumptions on the current status of RSI are made:
 An additional 10% of existing traffic signals need to be deployed, and an additional
100% of the existing other RSI need to be deployed.
 70% traffic signals exist but require an upgrade, and 25% other infrastructure exist but
require an upgrade. (Ricardo Energy & Environment, 2020)
An EU stock of RSI that need to be installed as new and upgraded is calculated based on
the assumptions above and the currently installed stock, estimated from a US connected
vehicle infrastructure footprint analysis (U.S. DOT, 2014). The number of RSI units
deployed and upgraded scales linearly with the service availability.
Ongoing costs
The annual ongoing costs per unit for public authorities are broken down into:
 Regular ITS station maintenance is assumed to be 5% of the capital cost per year.
Several studies have cited this percentage for maintenance, such as the COBRA study
and US focussed NHTSA US DoT Connected Vehicle Field Infrastructure Footprint
Analysis (TNO, 2013) (NHTSA, 2014)
 Regular maintenance for RSI units is assumed to be 10% of the capital cost per year.
This is an average based on the EU EIP evaluation reports and Member States National
ITS Reports. It is worth noting that the maintenance costs may vary depending on the
service provided as noted in the German report that this value is significantly too high
150
https://www.itskrs.its.dot.gov/costs
103
for network control systems, while the estimated value applies relatively well for route
control systems. However, the same figure is used in the assessment for simplicity.
 Power consumption: In the C-ITS Deployment study, the power consumption cost per
year was estimated at €18.40. This was derived from stakeholder input.
 Data costs, are based on the COBRA study, and are calculated to be €200 per year, per
new roadside ITS sub-system (TNO, 2013). Half this figure has been used (€100 per
year), to account for the assumption that half of the units will have wired backhaul and
therefore do not incur cellular data costs.
 Secure communications: An extensive study was carried out by the US DoT to assess
the cost of secure communications. It assumes that a security credentials management
system will need to be developed and implemented (most likely by a private company)
and suggests an annual cost of $50 per roadside unit to keep security credentials up to
date (NHTSA, 2014). This is equivalent to €37.91 per year.
Central ITS sub-systems
A central ITS sub-system is necessary to collect, process, and store mobility data in order
to create value and enable the delivery of effective ITS services. Two main components
are considered: NAPs and traffic management centres (TMCs).
While NAPs already exist in almost all Member States, it is necessary to upgrade the NAPs
to ensure that the data architecture supports the data categories to deliver all types of ITS
services. TMCs do not exist throughout all Member States and in some cases new TMCs
will need to be developed while other may require upgrading. In addition to the TMC and
NAP installation upgrade costs, ongoing costs related to maintenance and data collection
and management will also be incurred by public authorities.
Concerning private operators, investment is required to initially develop the backend
system (e.g. cloud, service provider platform), as well the ongoing operation and
maintenance costs. However, these costs vary significantly between different private
operators and collecting specific cost data is difficult and is not representative of all
operators. In addition, private operators will take a commercial approach to developing
their own systems and will only do so where there is a business case (i.e. balancing their
investment with the revenue generated by their services). Therefore, in the assessment only
the central ITS sub-system costs relevant to public authorities are considered.
A summary of the upfront and ongoing costs associated with central ITS sub-systems are
included in the table below.
Table 44: Breakdown of costs for central ITS sub-systems
Cost item Input Unit Cost
owner
Relevant
bundles
Upfront costs
NAP set up €273,500 Per NAP Public
body
1A, 1B, 2, 3, 4, 5
TMC installation and integration €2,500,000 Per
TMC
Public
body
1A, 1B, 2, 3, 4, 5
104
Cost item Input Unit Cost
owner
Relevant
bundles
TMC upgrade €175,000 Per
TMC
Public
body
1A, 1B, 2, 3, 4, 5
Ongoing
costs
NAP Maintenance €2,000,000 Per NAP Public
body
1A, 1B, 2, 3, 4, 5
TMC Maintenance €250,000 Per
TMC
Public
body
1A, 1B, 2, 3, 4, 5
Data Collection - MMTIS €600,000 Per NAP Public
body
1A, 1B
Data Collection - RTTI €1,000,000 Per NAP Public
body
1B, 2
Data Collection - SRTI €300,000 Per NAP Public
body
2, 3, 4, 5
Data Collection – S&S Truck Parking €100,000 Per NAP Public
body
3
Integration of transport providers on
NAP
€17,946 Per NAP Public
body
1A
Upfront costs
NAP set up
Following various EU Delegated Regulations, EU Member States are obliged to set up
NAPs to facilitate access, easy exchange and reuse of transport related data, in order to
help support the provision of EU-wide interoperable ITS services to end users. Member
States are free to decide which form their NAP will take. Across the EU, NAPs can either
be databases, data warehouses, data marketplaces (i.e. supported by private providers),
repositories, and registers, web portals or similar depending on the type of data concerned.
The cost to set up the data architecture is dependent on the NAP approach taken. In the
assessment the median value from the evaluation of the ITS Directive of €273,500 has
been used.
According to the annual NAP report (EU EIP, 2021), NAPs are operational in most EU
Member States for each type of data. In the assessment, the NAP set up cost only applies
to those Member States that have not already established an NAP and it is assumed that
only one NAP is required to support all service bundles such that the maximum stock is
one per MS. The upgrade of NAPs, to consider new data categories or road networks, is
considered in the ongoing costs.
TMC Installation and Upgrade
It is assumed that roadside ITS infrastructure will be connected to a TMC. In line with the
C-ITS Deployment Study, the two costs relevant to deploying TMCs are the cost for
developing a TMC interface for each Member State and an interface to local traffic
controllers for roadside ITS infrastructure. Both of these costs combined are estimated to
be €2,500,000, which includes integration costs.
In some cases, TMCs will already exist but will need to be upgraded to ensure they are at
a sufficient operational standard. From the Hungarian ITS report, a modernisation of a
TMC was reported to cost approximately €175,000. Each TMC may not require the same
105
level of investment, but in the assessment the same value has been assumed for all TMC
upgrades.
These costs are associated with all bundles but will only need to be applied once as the
TMC will jointly facilitate the provision of all services. The following assumptions on the
current status of TMCs are made:
 The total number of TMCs needed across Europe equals the number of urban nodes
(500), distributed between the country groupings by total road length.
 15% of the total are fully operational and do not need upgrading. This value is
estimated from the current number of core urban nodes divided by the extended number
of urban nodes.
 For Front Runners countries, 25% of total TMC stock needs to be installed (75%
upgraded), for Planned Adopters 50% of total TMC stock needs to be installed (50%
upgraded) and for Followers 75% of total TMC stock needs to be installed (25%
upgraded).
The number of TMC units installed and upgraded scaled linearly with service availability.
Ongoing costs
NAP maintenance
NAP Maintenance costs include upgrades to accommodate new or evolving data types,
data delivery, data storage and personnel to operate the NAP and fix problems that may
arise. The total cost for data storage depends on the penetration of data accessibility on
roads and the amount of data to be stored according to the characteristics of each data
category. In line with the operating costs of the Italian NAP, this cost has been estimated
at €2,000,000 per NAP. This can be considered as a representative value, despite the fact
that the overall operating costs for NAPs vary significantly151
.
TMC Maintenance
The cost for maintaining the TMC back-office and local controller interfaces is estimated
at 10% of capital costs based on the COBRA study (TNO, 2013), or €250,000 per TMC.
Data collection
This cost category considers the additional personnel that would need to be involved in the
additional data collection that might be required and the expected costs for making
available data accessible in the correct format. The costs were determined from stakeholder
input and an assessment of the size of data categories and the respective number of data
providers. They are estimated to be:
 MMTIS : €600,000 per year
151
AT reported an operating cost of €10,000 per year while NL reported an operating cost of €10,000,000
per year.
106
 RTTI : €1,000,000 per year
 SRTI : €300,000 per year
 S&S truck parking : €100,000 per year
Although the data collection is applicable to more than one bundle, each cost will only
apply once as the data collection process only occurs once to ensure the data is in the
correct format to be used to provide different services. These costs are in line with the cost
for operating the Italian NAP, which has a fully operational NAP for all data categories,
receiving information from 144 parties that includes bilateral agreements with 14 of them.
The total ongoing costs for the NAP was reported at €4,000,000, in line with the estimates
used in this assessment (including NAP maintenance). This is assumed to be a middle
range value, as NL and AT reported ongoing costs for NAPs of €10,000,000 and €10,000,
respectively.
Integration of transport providers on NAP
It is necessary to integrate transport providers on the NAP to facilitate the services that fall
under Bundle 1A. Each service provider that is integrated will share data with the NAP in
the correct format so that multimodal services can be facilitated. According to stakeholders
during the interviews, this typically requires 1-2 person months. For simplicity, it has been
assumed that each Member State will employ one person to conduct the integration of
transport providers. Hence, the cost is estimated at 1 FTE per NAP, which is equal to
€17,946.
5. PRIMARY INPUT DATA
5.1. Bundle 1a- Multimodal travel information service
Service Overview
Multimodal digital mobility (MDM) services provide European travellers with
comprehensive door-to-door information allowing for well-informed travel decisions
according to their needs. It seamlessly integrates information from different transport
modes, based on a strong backbone of rail and local public transport.
The development of MDM services will enable the development of a more efficient
transport system; it will widely benefit citizens, as, for example, it is not always easy to
get the right information about cross-border transport and connections; it should also allow
for the possibility to go for a journey that least affects the environment.
Delegated regulation (EU) 2017/1926 stipulates that each Member State shall set up a
NAP, which constitutes a single point of access for users to at least the static travel and
traffic data and historic traffic data of different transport modes. This includes modes such
as air, high-speed rail, conventional rail, maritime, metro, tram and bus. Such data can be
used by either public bodies or private operators to provide the multimodal travel
information service to the user.
Impacts
107
Effective multimodal travel information services are significant for both travellers and
operators. Such systems make it easy for travellers to find and use the best means of
transport available. They help operators to run their systems and reduce the costs of
interacting with travellers. Multimodal travel information services are important for
encouraging the use of sustainable transport and for making efficient use of the road system
in future. Thus, in addition to providing benefits for travellers and operators, multimodal
travel information services can also contribute to high level public policy objectives such
as reducing congestion and emissions and improved network management through modal
shift away from private car use to public transport and active modes.
In general, there is limited evidence of the impacts of multimodal travel information
services, although it is widely accepted that it has a positive effect on congestion and modal
shift. The main sources of information for the impacts of this service have been the Study
on ITS Directive, Priority Action A: The Provision of EU-wide Multimodal Travel
Information Services (TRL, 2016) and a literature review carried out by KiM Netherlands
Institute for Transport Policy Analysis (KiM, 2018).
Table 45: Overview of key data source – Study on ITS Directive, Priority Action A: The Provision of EU-
wide Multimodal Travel Information Services
The objective of the study overall was to support the European Commission in the
development of a policy framework to enable the provision of EU-wide multimodal travel
information services. A detailed Cost Benefit Analysis (CBA) was conducted by looking at
different scenarios in which different elements of potential policy measures are considered.
The assessment took account of the economic, social, environmental, and market impacts
that the policy options might have over a 15 year period (2016-2030), with implementation
of the different elements phased in over varying timescales. Using input from experts
nominated by Member States and existing services, the study identified the implementation
and operational costs associated with the key deployment measures.
Safety
The primary effect of Multimodal Travel Information Services is expected to be on
congestion/travel time and modal shift; hence the safety impacts are expected to be
minimal. No safety impacts are therefore anticipated on an EU level as a consequence of
this service and it is not included as part of the model.
Fuel Consumption
The primary effect of Multimodal Travel Information Services is expected to be on
congestion/travel time and modal shift; hence the fuel consumption impacts at an
individual user / vehicle level are expected to be minimal. However, there might be an
impact on fuel consumption at the overall transport system level as a result of modal shift.
While this is not included directly in the model, the impact is reflected through the modal
shift that is captured in the model.
Emissions
108
The primary effect of Multimodal Travel Information Services is expected to be on
congestion/travel time and modal shift; hence there is an associated emission impacts at an
individual user / vehicle level. While this is not included directly in the model at an
individual user level, the impact is reflected through the modal shift that is captured in the
model.
Congestion/Travel Time
From the study on Provision of EU-wide Multimodal Travel Information Services, a
number of assumptions/estimates were made on the improvement of travel time152
:
 EU-wide journey planning services would enable people travelling across borders
to save time while planning their journey; a 10-minute time saving was assumed
per trip.
 EU-wide journey planning services with dynamic information would enable people
travelling across borders by rail to save time during disrupted trips as in some cases
it is possible to revise the journey plan to reduce the impact of disruption. 3% of
rail trips were estimated to be disrupted, 20% of these were assumed to be re-
planned, with a 30-minute time saving assumed per re-planned trip.
 It was assumed that air passengers would not be in a position to revise their journey
plans during disrupted trips and that passengers using other modes would not be in
a position to save time in the case of delays of less than 30 minutes.
 It was assumed that improved access to real-time passenger information would
result in a 5-minute journey time saving for some delayed ‘infrequent’ bus services
(defined here to be those with a headway over 15 minutes). Taking into account
the number of bus journeys that are delayed each year and the access to dynamic
information via smartphones, it was assumed that 20% of public transport trips
were on infrequent services and 30% of these were equipped with real-time
information. However, the provision of such information through other channels
(such as smartphones) would improve accessibility to a small proportion of users.
As such, the 5-minute journey time saving was assumed to be applied to 1% of
these trips.
In addition to this, modal integration can decrease the average use travel times and increase
urban public transport network efficiency, as shared bikes are used for first and last miles.
Modal Shift
Similarly, the study on Provision of EU-wide Multimodal Travel Information Services
made assumptions on the improvement of modal shift for the last leg of the outward
journey and first leg of the return journey in cross-border scenarios. The following shifts
to more sustainable modes are expected to reduce congestion and emissions and improve
air quality:
152
Please note the main focus of this study was EU-wide service and therefore the impacts generally focus
on cross-border activities, although not exclusively
109
 Travelling from airports, 5% of trips were assumed to switch from taxi or hire car
to public transport, with an average distance of 10km between airport and final
destination.
 Travelling from train stations, 12% of trips were assumed to switch from taxi to
public transport with an average distance of 5km between train station and final
destination.
There have been a number of private operators that have conducted surveys with their users
on their travel behaviour. While serving as a useful indicator for the volume of users that
have increased their use of sustainable or active modes, it is often difficult to discern the
change in modal share of their journeys. The Austrian research project SMILE, which
piloted a multimodal travel information tool that combined new mobility modes with
traditional forms of transport, identified behaviour change amongst its users, including:
 48% respondents increased usage of public transportation (urban public transport
26%, regional public transport 22%)
 10% increased the use of bike sharing offers while
 4% increased the usage of e-car sharing as well as another
 4% increased the usage of e-bike/pedestrians
 Overall, 21% of the surveyed pilot users stated to have reduced the usage of their
private car
5.2. Bundle 1a - Multimodal travel information and booking/re-selling service
(MaaS)
Service Overview
MaaS is defined as integration of various forms of transport services into a single mobility
service accessible on demand. For the user, MaaS can offer added value through use of a
single application to provide access to mobility, with a single payment channel instead of
multiple ticketing and payment operations. There are several levels of integration for the
full definition of MaaS to be met:
 Integration of information (this is the same as MMTIS)
 Integration of booking and payments
 Integration of the services offer (e.g. bundling / subscription) – although certain
national legislations have lighter definitions. For example, France define MaaS
only as a digital service to enable the integration & selling of mobility services
(L'Assemblée nationale, 2019).
A successful MaaS service also brings new business models and ways to organise and
operate the various transport options, with advantages for transport operators including
access to improved user and demand information and new opportunities to serve unmet
110
demand. The aim of MaaS is to provide an alternative to the use of the private car that may
be as convenient, more sustainable, help to reduce congestion and constraints in transport
capacity, and potentially more cost effective.
Deployment
Since MaaS was first described in 2014, many mobility initiatives have labelled themselves
as MaaS but do not meet all levels of integration. There are limited examples of fully
fledged MaaS in Europe - the most notable platforms are UbiGo153
and Whim154
. There
are many more platforms that provide only some level of integration, but these are
increasingly adding a subscription/bundling integration to the platform. However, even if
some MaaS initiatives have been piloted across Europe, so far most of them had problems
reaching a significant scale and stable business operation, and there is still a lack of a solid
MaaS experience replicable at the EU level. Thus, the uptake to date has been slower than
expected.
The development of MaaS is dependent on technological, societal, market and governance
developments and as such the timeline for wider adoption remains unclear. However, as
knowledge on the challenges that are faced by MaaS operators and how to better address
them improves, it is expected that most large EU cities will have MaaS by 2025155
.
Impacts
Given that there are only a few cases of fully-fledged MaaS and small-scale pilots, the
information on impacts is limited and largely hypothesised. As highlighted earlier, the
major impact is modal shift, with secondary impacts expected on congestion / travel time.
Safety
The primary effect of MaaS is expected to be on modal shift, hence the safety impacts are
expected to be minimal. Although improvements of traffic safety are sometimes mentioned
in literature as potential impact of MaaS156
, it is not seen as one of the major benefits MaaS
could offer. No safety impacts are therefore anticipated on an EU level as a consequence
of this service and it is not included as part of the model.
Fuel Consumption
The primary effect of MaaS is expected to be on congestion/travel time and modal shift;
hence the fuel consumption impacts at an individual user / vehicle level are expected to be
minimal. However, there might be an impact on fuel consumption at the overall transport
system level as a result of modal shift. While this is not included directly in the model, the
impact is reflected through the modal shift that is captured in the model.
Emissions
153
Operating in two cities in Sweden
154
Whim operates in five European cities but only offers bundling/subscriptions in one of these services.
155
From ITS Virtual Congress
156
https://www.theiet.org/media/3666/mobility-as-a-service-report.pdf
111
The primary effect of MaaS is expected to be congestion/travel time and modal shift; hence
the emission impacts at an individual user / vehicle level are expected to be minimal.
However, there might be an impact on emissions at the overall transport system level as a
result of modal shift.
Congestion/Travel Time
The potential of MaaS to reduce (single-occupancy) car trips and stimulating a shift
towards public, shared and active transport may result in a reduction in traffic congestion.
The extent to which MaaS reduces congestion is heavily dependent on the design of the
MaaS schemes implemented. In case the deployment of MaaS schemes lead to increased
used of car and ride sharing schemes resulting in additional car trips and undesired shifts
from public transport, congestion may even stay at the same level or increase157
.
Modal Shift
The main source of impact data is the literature review of MaaS and changes in travel
behaviour preferences published by the Dutch Ministry of Infrastructure and Water
Management158
. The study identifies a number of modal shift impacts for each service
provided by a given mobility platform. The impacts of each these services are presented
below.
Impact of car sharing
The literature review study found that car sharing:
 is accompanied by an average decline in VKT/VMT (Vehicle Kilometres
Travelled/Vehicle Miles Travelled) of between 27 and 43% per year. Reducing
private car use is less likely to occur in suburban car sharing members than urban
car sharing members
 between 9 and 13 privately owned vehicles were taken off the road per (station-
based) car-sharing vehicle.
Impact of bike sharing
The literature shows that the impact of bike sharing on shifting private car use is highly
contextual. Around 2% of users in London substituted cycling for private car use, which
contrasts with rates of between 19-21% in Minneapolis, Melbourne and Brisbane. The
study also found that most people who switch to shared bikes come from walking and PT,
not from cars. It was found that in Dublin 77% of the total who had switched originally
used walking, 16% from bus/tram and the remainder from taxis.
Overall impacts of MaaS
Results of MaaS schemes have shown that:
157
https://www.theiet.org/media/3666/mobility-as-a-service-report.pdf
158
https://www.researchgate.net/publication/330958677_Mobility-as-a-
Service_and_changes_in_travel_preferences_and_travel_behaviour_a_literature_review
112
 In Vienna, 21% of participants reduced their use of private cars
 In Sweden, 44% of UbiGo participants decreased their use of private cars.
The literature review also found an expected increase of 14% and 17% of cycling due to
MaaS for regular public transport and car users, respectively. From the regular car users,
12% expects to walk more as part of their trips if MaaS is implemented. As for public
transport, there may be a risk that the implementation of MaaS shifts regular cyclists (or
pedestrians) to other modes.
5.3. Bundle 1b - Travel Information Service (Road)
Service Overview
Travel information service provides the European traveller with door-to-door information
for well-informed travel decisions (pre-trip) using static data. Travel information is offered
by both public and private providers. It is therefore necessary to clarify the roles and co-
operation of both sides. The future role of road operators as content providers is unclear
today. With increasing mobile phone and vehicle tracking, private service providers can
be better informed about the traffic situation than the road operator.
Delegated regulation (EU) 2015/962 stipulates that Member States should make available
static data (as well as dynamic data and traffic data) through their NAP. This includes data
such as physical attributes of the road network, road classification, speed limits, traffic
signs reflecting traffic regulations and identifying dangers, and location of tolling stations
and tolled roads. Such data can be used by either public bodies or private operators to
provide the travel information service to the user either via webpage or smartphone.
Impacts
The main data sources for the impacts of the travel information service were the
eSafetyForum Intelligent Infrastructure Working Group’s Final Report (eSafetyForum,
2010), the iMobility Effects Database (eSafety and iCarSupport, n.d.) and the TNO report
on the impact of information and communication technologies on energy efficiency in the
road transport sector (TNO, 2009).
Traffic efficiency
The only report to assess traffic efficiency was the eSafetyForum report. This reported
results for three related services: real time event information, real time traffic condition
information, and travel time information. All services show a 1-15% reduction in
congestion. In the absence of more precise data, the mid-point of this range was used for
the modelling, i.e. an 8% improvement in traffic speed for both passenger and freight
vehicles, and it has been assumed that the impact is the same across all road types.
Fuel consumption and CO2
The eSafetyForum report presents results for three services: real time event information,
real time traffic condition information, and travel time information, which all show a 1-
10% reduction in fuel consumption/CO2 emissions. Further information about this service
113
is not given and the report does not state whether these are the expected benefits at an EU-
level.
In a study performed by TNO on the impact of information and communication
technologies on energy efficiency in the road transport sector (TNO, 2009), a service called
‘fuel efficient route choice’ was assessed. This was calculated to have a 2.1% impact on
fuel consumption at an EU level. As the emphasis of this service was on maximising fuel
efficiency, rather than shortest journey time, the fuel savings benefits are expected to be
lower than this value.
Another similar service assessed by TNO is the freight specific, trip departure planning
service. The objective of this service is to ensure fleet journey time is minimised, based on
real, current and predicted traffic conditions. This is a similar function as the traffic
information and smart routing service defined in this report. In the TNO study, the trip
departure planning service was estimated to have a 1.8% (reduction) impact on fuel
consumption/CO2 emissions at an EU level, if implemented in all freight vehicles.
Due to limited other data for the traffic information and smart routing service, an average
of the figures stated for the two TNO services was used and applied to all vehicles (except
public transport) and road types. This gives a 1.95% impact on fuel consumption/CO2
emissions for passenger and freight vehicles across all road types. This figure is supported
by the iMobility Effects Database, which reports a 2% impact on CO2 emissions at an EU
level. (eSafety and iCarSupport, n.d.)
Environmental and emissions impacts
No data was identified for this impact category in the reports reviewed, therefore emissions
impacts were scaled using the ratio between fuel/CO2 impacts and emissions impacts for
the in-vehicle speed limit service in urban areas (see section 5.13.2). This resulted in the
following impacts on emissions:
 NOx: 0.4% reduction on motorways, 1.7% reduction on other interurban roads,
0.5% reduction on urban roads
 PM: 0.3% reduction on motorways, 0.8% reduction on other interurban roads, 0.1%
reduction on urban roads
 CO: 0.2% reduction on motorways, 4.2% reduction on other interurban roads, 2.3%
reduction on urban roads
 VOCs: No impact.
Safety
No data was identified for this impact category in the reports reviewed. It is likely that this
service could indirectly lead to safety benefits due to reduced driver hesitation and reduced
congestion, however no reports quantify this effect. In the modelling this service is
assumed to have no impact on safety.
Modal Shift
114
The primary effect of Travel Information Services is expected to be on congestion/travel
time; hence the modal shift impacts are expected to be minimal. No modal shift impacts
are therefore anticipated on an EU level as a consequence of this service and it is not
included as part of the model.
5.4. Bundle 1b - Real-time traffic information service
Service Overview
Real-time traffic information (RTTI) services aim to provide road users with useful,
accurate and up-to-date information on the road network, traffic circulation plans, traffic
regulations, recommended driving routes and real-time traffic data including estimated
travel times, information about congestion, accidents, road works and road closures.
Additionally, real-time traffic information services can potentially include any other
information considered relevant to the planning and the execution of the trip. While there
are many similarities with Travel Information Services (see section 5.3), real-time traffic
information has a broader scope of data categories with more emphasis on data being made
available in real-time such that drivers can receive information en-route.
As per Article 3(1) in Delegated Regulation (EU) 2015/962, Member States are required
to set up a national access point, which constitutes a single point of access for users to the
road and traffic data, including data updates, provided by the road authorities, road
operators and service providers and concerning the territory of a given Member State. The
specific data categories are listed in the annex to the delegated regulation. Such data can
be used by either public bodies or private operators to provide the service to the end user
via a smartphone or in-vehicle system.
Impacts
The main data sources for the impacts of the RTTI service were the evaluation reports of
the CEF funded ITS Corridors on the EU EIP website. The five CEF funded ITS corridors
have focused on the harmonisation of specifications and deployment of traffic management
services. The evaluation library (EU EIP) gathers all available Evaluation Reports,
guidance and source materials in one place and has been regularly updated throughout the
duration of the activities to date. By the end of 2019, 35 EU EIP compliant evaluation
reports from the current ITS Corridors were available via the EU EIP Evaluation Library.
These are supplemented by an extensive archive of over 80 archive evaluation reports and
guidance documents in an archive gathered from previous programmes.
Each report presents the deployment, benefit and cost KPIs following the evaluation report
template developed by EU EIP.
While it is very likely that there is a positive impact of RTTI, it is not straightforward to
assess the impact in quantitative terms because the ‘application’ of RTTI is not sharply
defined, limited empirical results exist and other traffic management, traffic control and
cooperative vehicle safety systems target the same factors as RTTI.
Traffic efficiency
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In the RTTI study (VVA, coffey, TiS, 2020), Finland reported an improvement in travel
time of 1.1% while Netherlands reported an improvement in travel time of 9%. These
figures are assumed to represent two extreme cases (high and low) and thus have taken a
median value. Converting this to increase in speed leads to figure of 5.3%. In the absence
of any further data, this impact is assumed to apply to all road types equally.
Fuel Consumption
From the ex-ante evaluation of the NEXT-ITS corridor (EU EIP, 2018), the average effect
of real-time traffic information on users on equipped sections was:
 1% reduction in CO2 emissions (traffic conditions and travel time)
 0.05% reduction in CO2 emissions (road weather)
Similarly, Finnish authorities reported a 1.2% decrease in CO2 emissions as a consequence
of RTTI. Hence, to accommodate both of these sources, the impact has been determined
to be 1.1% for all vehicle types, excluding public transport for which the impact is assumed
to be zero. In the absence of data for different road types, the same impact has been applied
across each part of the road network.
Emissions
No data was identified for this impact category in the reports reviewed, therefore emissions
impacts were scaled using the ratio between fuel/CO2 impacts and emissions impacts for
the in-vehicle speed limit service in urban areas (see section 5.13.2). This resulted in the
following impacts on emissions:
 NOx: 0.2% reduction on motorways, 1.0% reduction on other interurban roads,
0.3% reduction on urban roads
 PM: 0.2% reduction on motorways, 0.5% reduction on other interurban roads, 0.1%
reduction on urban roads
 CO: 0.1% reduction on motorways, 2.4% reduction on other interurban roads, 1.3%
reduction on urban roads
 VOCs: Not included as an impact due to in-vehicle speed limits resulting in an
increase of VOC’s as a consequence of increased braking. The same logic does not
apply to travel information services and therefore the same ratio between fuel/CO2
impacts and emissions cannot be applied.
Safety
From the ex-ante evaluation of the NEXT-ITS 2 corridor (EU EIP, 2018), the average
effect of real-time traffic information on users on equipped sections was:
 0% reduction in fatal and injury accidents (traffic conditions and travel time)
 1.5% reduction in fatal and injury accidents (road weather)
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Hence, an impact value of 1.5% for TEN-T network and motorways has been used for all
accident types for both passenger cars and trucks, while the impact on public transport is
expected to be zero. The impact on safety has been scaled for interurban and urban roads
in line with the impact observed for SRTI services, as the nature of each service is similar.
This results in 1% for light injuries and material damages.
Modal Shift
RTTI services focus on real-time information for the road network and does not capture
data from other modes. Hence, the model shift impacts are expected to be minimal. No
modal shift effects are therefore anticipated on an EU level as a consequence of this service
and it is not included as part of the model. This is confirmed by the supporting study report
(VVA, coffey, TiS, 2020) and the ITS Corridor evaluations (EU EIP, 2018), which did not
consider the effect on modal shift for this service.
5.5. Bundle 1b - Parking and pricing information
Service overview
Parking and pricing information services aim to provide road users with useful, accurate
and up to date information of the parking options in a given area. This includes on street
parking, off street parking, and park and ride facilities. Information made available through
these services includes static data (such as type and location of parking) and dynamic data
(such as price and availability of parking) and the service can be delivered either via a
smartphone or in-vehicle system. The provision of on-street and off-street parking
information is intended to bring efficiency benefits to drivers and help to reduce emissions
by reducing the time spent ‘cruising’ at low speeds. In the case of Park & Ride information,
it helps to reduce congestion in urban areas and also shift travel from cars to public
transport.
Impact data
In general, there are limited data sources for each of the services within this service type:
 On street parking information: The only data source which covered the potential
impacts of the on-street parking information service was the eSafetyForum
Intelligent Infrastructure Working Group’s Final Report. The information from this
report was supplemented by additional desk research into the provision of parking
information services and the time spent searching for parking spaces. A number of
reports were used to estimate the impact of this service from first principles, as
referenced below.
 Off street parking information and management: No other publicly available
studies that specifically examine off street parking information were identified.
Impacts for off street parking were assumed to be similar to on street parking,
therefore the same values have been used as inputs to the modelling.
 Park & Ride Information: No other publicly available studies that specifically
examine the impacts of this service were identified.
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Given that there is no distinction between the impacts for on-street and off-street parking
and no data available for park & ride services, all services have been streamlined into one
group such that they only present one set of impacts.
Traffic efficiency
Traffic efficiency improvements are expected to be the main benefit of this service. No
data was identified for this impact category in the reports reviewed. The following
methodology was therefore used to estimate impacts on traffic efficiency from first
principles:
 Identify the time spent looking for a parking space in a Member State.
o In France, an estimated 70 million hours per year is spent ‘cruising’ trying
to find parking (Gantelet & Lefacounnier, 2006) .
 Scale this to EU level, based on total vehicle kilometres driven in urban areas
(based on data for the EU-27 from TRT’s ASTRA model).
o Gives an estimated 450,272,549 hours ‘cruising’ per year for the EU
 Apply an effectiveness factor to the parking information C-ITS service.
o 3.5 times less time spent cruising for parking to final destination when
parking information is shown (or a 71% effectiveness), according to a
report published by the University of Zurich (Tsiaras, et al., 2015).
o Use this number to estimate the total change in time spent driving on urban
roads from deploying parking information services to all vehicles at an EU
level.
o 0.61% reduction in travel time/improvement in speed in urban areas across
passenger and freight vehicles.
Park and ride schemes are designed to reduce congestion in urban areas, therefore some
traffic efficiency impacts are to be expected. However, these urban efficiency gains do not
occur directly with the vehicle using the service, since the impact of the service will be to
increase the likelihood of the vehicle in question using Park & Ride services – thereby
preventing it entering the congested urban area. This makes it very difficult to estimate the
impact on efficiency from first principles. In the absence of any data for this impact
category in the reports reviewed, it was assumed that this specific service would have zero
impact on speed in urban areas.
Fuel consumption and CO2
The average speed of vehicles when ‘cruising’ for parking spaces in urban areas was
estimated at half the average speed limit for urban areas (Tsiaras, Hobi, Hofstetter, Liniger,
& Stiller, 2015), i.e. 15 kph in the EU.
This speed was used as an input to Ricardo Energy and Environment’s speed-emissions
curve model, which is able to estimate the impact in g/km on CO2/fuel consumption, NOx
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and PM10 emissions. Using the total time spent ‘cruising’ and average speed of ‘cruising’
referenced above, a total EU-level cruising distance could be determined, from which the
total EU-level emissions impacts could be estimated.
The total resultant improvement in fuel consumption and CO2 emissions was estimated
from the above methodology as 0.79% across passenger vehicles in urban environments.
Environmental and emissions impacts
NOx and PM emissions were estimated using the same speed-emissions curve model as for
fuel consumption/CO2. Total improvement in NOx and PM emissions were estimated at
0.26% and 0.07% respectively across all passenger vehicles in urban environments.
For CO and VOC emissions, these were assumed to be proportional to fuel consumption
savings, and therefore estimated at a 0.79% reduction for urban passenger vehicles.
Safety
The eSafetyForum reports that parking information and guidance will have zero impact on
safety (eSafetyForum, 2010). Whilst there may be secondary impacts due to reduced
congestion in urban areas, no data exists to support this and the safety impacts were
therefore assumed to be zero.
Modal Shift
The on-street and off-street parking information is likely to encourage users to continue
using private cars in urban areas and therefore it is not expected to have any impact on
modal shift. However, park & ride information will increase the likelihood of the vehicle
in question using Park & Ride services – thereby preventing shifting part of the journey to
public transport and other active modes while in the city. In the absence of data, it is not
possible to identify the extent of this impact.
5.6. Bundle 1b - Recharging/refuelling location and pricing information
Service Overview
Recharging and refuelling location and pricing information services aim to provide users
with the associated information, ensuring that the information is accurate and up to date.
This includes static data (location and conditions for use) and dynamic data (availability
of recharging point), which is delivered as a service either through a smartphone or in-
vehicle system. Data made be made available through NAPs as per Delegated Regulation
(EU) 2015/962.
This service allows users to be informed of and book charging point time windows for
fuelling and charging stations for alternative fuels. This enables a more convenient driving
experience and allows for vehicle owners to plan routes according to the location of
appropriate refuelling points; eBilling information may also be included. This service is
applicable on all road types and is currently focused on cars, bringing vehicle operation
and efficiency benefits. As technologies advance and fleet composition changes, this
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service will be applicable to additional vehicle types. However, it is not expected to have
any impact on modes outside of road transport.
Impacts
The primary impact of this service is to provide users with adequate information as many
users often lack information on where they can recharge/refuel and the availability of
recharging/refuelling points – thereby making journeys more comfortable for the user and
encouraging the uptake of alternatively fuelled vehicles. This service also impacts the
journey time and route planning as users do not have to spend time cruising in search for
an available recharging/refuelling point. In the model, only the impacts on travel time are
considered.
Congestion/Travel Time
End-users are expected to save time in finding recharging and refuelling stations due to
higher aggregation of data. Although detailed data is not available, EV users are expected
to recharge once per week, with an estimated 10 minutes saved per recharging event due
to the increased accessibility of information about the availability of recharging points.
Other AFV users (e.g. hydrogen) are estimated to refuel once every 2 months and expected
to again save 10 minutes per refuelling event (VVA, coffey, TiS, 2020).
In absence of any more specific data, the same impact as parking information has been
used, due to the similar nature of these services. That is, a 0.61% increase in average speed
in urban areas for passenger cars (noting that this only applies to alternatively fuelled
vehicles). The impact of this service is expected to be negligible outside of urban areas
given that recharging/refuelling points will be located in service stations along motorways
and therefore do not cause an issue for users in locating them. Furthermore, this impact
does not apply to trucks or public transport vehicles as they will use private infrastructure
in urban areas.
Fuel Consumption
The primary impact modelled in this IA is congestion/travel time. Although this will have
a minor impact on the overall fuel consumption, the effects are expected to be minimal and
therefore have not been considered in the model. This is confirmed by the RTTI study
report, which did not consider the effect on fuel consumption for this service (VVA, coffey,
TiS, 2020).
Emissions
The primary impact modelled in this IA is congestion/travel time. Although this will have
a minor impact on the overall emissions, the effects are expected to be minimal and
therefore have not been considered in the model. This is confirmed by the RTTI study
report, which did not consider the effect on emissions for this service (VVA, coffey, TiS,
2020).
Safety
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The primary impact modelled in this IA is congestion/travel time, hence the safety impacts
are expected to be minimal. No safety effects are therefore anticipated on an EU level as a
consequence of this service and it is not included as part of the model. This is confirmed
by the RTTI study report, which did not consider the effect on safety for this service (VVA,
coffey, TiS, 2020).
Modal Shift
The primary impact modelled in this IA is congestion/travel time; hence the modal shift
impacts are expected to be minimal. No modal shift effects are therefore anticipated on an
EU level as a consequence of this service and it is not included as part of the model. This
is confirmed by the RTTI study report, which did not consider the effect on modal shift for
this service (VVA, coffey, TiS, 2020).
5.7. Bundle 2 - Traffic network management systems
Service Overview
Traffic network management systems refers to the combination of measures that serve to
preserve traffic capacity and improve the security, safety and reliability of the overall road
transport system. These measures make use of ITS systems and services in day-to-day
operations that impact on road network performance. Traffic network management
systems encompass a number of services, for example variable speed limits, dynamic lane
management and traffic incident management.
Road operators utilise a range of sensor deployment and data types such as RTTI and SRTI
to monitor traffic performance and implement services accordingly. Traffic network
management systems are employed at the network level and delivered to all users on the
road through variable message signs.
Impacts
Traffic network management systems have an impact across environmental, safety and
traffic efficiency categories. It is difficult to state which of these is considered to be the
primary impact, as different services are delivered in response to certain events or
conditions. However, most often they are designed to improve traffic efficiency. Given
that these services are deployed at a network level, the impact is the same across all vehicle
types.
The key sources for these impacts are the evaluation reports of CEF funded ITS corridors.
The five CEF funded ITS corridors have focused on the harmonisation of specifications
and deployment of traffic management services. The evaluation library (EU EIP) gathers
all available Evaluation Reports, guidance and source materials in one place and has been
regularly updated throughout the duration of the activities to date. By the end of 2019, 35
EU EIP compliant evaluation reports from the current ITS Corridors were available via the
EU EIP Evaluation Library159
. These are supplemented by an extensive archive of over 80
159
https://www.its-platform.eu/filedepot/folder/1077?_ga=2.79652372.1048593557.1623322084-
873712203.1621001876
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archive evaluation reports and guidance documents in an archive gathered from previous
programmes.
Each report presents the deployment, benefit and cost KPIs following the evaluation report
template developed by EU EIP. In many cases, the evaluation reports focus on a dedicated
section of the road network employing one type of service within traffic network
management systems. In such cases, these impacts have been aggregated to determine the
maximum possible impact of traffic network management systems.
Safety
The main impacts on safety are form the Arc Atlantique corridor, which deployed traffic
management services such as hard should running and lane control systems.
 In Paris sensors on the highway and access ramps and traffic lights on access
ramps were implemented in peri-urban setting. The expected result is up to a 20%
reduction in accident risk (EU EIP, 2020).
 In the UK, ‘smart motorways’ on the A2/M2 are expected to reduce personal
injury accidents by 55.7% since hard should running was introduced. There is also
an overall reduction in the severity of accidents with zero fatalities and fewer
seriously injured expected (EU EIP, 2017).
 Another section of road network (M25) providing variable speed limited and
hard should running (and RTTI and SRTI) has showed an improvement in safety
over a 12-month period. The results show a reduction of 67% (seriously injured);
55% (killed or seriously injured); 33% (slightly injured); 15% (FWI); 35% (total).
However, the evaluation notes that a conclusion on safety can’t be drawn as the
sample size after 12 months operation is too small (EU EIP, 2017).
 Overall, the impacts of the Arc Atlantique 2 Corridor are expect to reduce slight
injuries by 236 per year, seriously injured by 28 per year, and fatalities by 11 per
year (EU EIP, 2016).
 Another section on the M25 (providing the same services) was also evaluated over
a 12 month period. Vehicle Hours Delay (VHD) has reduced slightly overall in the
clockwise direction from 4,008 hours before the scheme was implemented, to 3,046
hours after the scheme went operational. This is a daily saving of 962 VHD. In the
anti-clockwise direction, it has reduced from 3,711 hours prior to scheme
implementation to 2,355 hours after the scheme came into operation. This is a daily
saving of 1,357 VHD. ) Furthermore, average journey time has improved clockwise
in most time slices. Anti-clockwise journey times in the PM peaks are greatly
improved but slightly worsened during the AM and inter-peak periods. Before the
scheme the clockwise journey time ranged from 11min 33sec to 16min 3sec and
after they ranged from 11min 30 sec to 15min 20sec depending on day and time of
day. The clockwise improvement in journey time ranges from -0.7% to 10.5%. In
the anti-clockwise direction journey time ranged from 11min 6sec to 15min 10sec
and after they ranged from 11min 15 sec to 13min 2sec depending on day and time
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of day. The improvement in journey time ranges from -4.5% to 13.3% (EU EIP,
2015).
From the evaluation of the NEXT-ITS 2 Corridor (EU EIP, 2018), the observed safety
impacts (in absolute numbers) are a reduction of 0.11 fatalities and 2.45 injury accidents
per year across the network. This is a result of VMS providing information on congestion,
incidents, accidents and other problems of the network.
Fuel Consumption
In France (part of the Arc Atlantique Corridor), a dynamic traffic management system
consisting primarily of VMS is activated when necessary to divert traffic. Two separate
sections were evaluated to find a total fuel saving of 2353.1 litres across both sections
including both LDVs and HDVs). This equates 6.25 tons of CO2 emissions.
Emissions
The following results were found in ex-ante evaluations specific sections of the Arc
Atlantique Corridor:
 In Paris, sensors on the highway and access ramps and traffic lights on access
ramps were implemented in peri-urban setting. The expected result is up to a 30%
reduction in polluting emissions (EU EIP, 2020).
 In the UK, ‘smart motorways’ on the A2/M2 are expected to reduce emissions by
up to 10% due to traffic running more smoothly.
From the evaluation of the NEXT-ITS 2 Corridor, the observed fuel emission impacts (in
absolute numbers) is a reduction of 11.5 kilotons of CO2 per year across the network. This
is a result of VMS providing information on congestion, incidents, accidents and other
problems of the network.
Congestion/Travel Time
The following results were found in ex-ante evaluations specific sections of the Arc
Atlantique Corridor:
 In Paris, sensors on the highway and access ramps and traffic lights on access
ramps were implemented in peri-urban setting. The expected result is up to a 15%
reduction in travel time during peak traffic and increase in average speed of 10km/h
during peak periods. Another evaluation of a similar service deployment on a
different part of the corridor found that each user has gained 6 minutes of travel
time per day (EU EIP, 2020).
 In the UK, ‘smart motorways’ on the A2/M2 indicate an improvement of journey
time reliability by 22% (EU EIP, 2017)
 Another section of road network (M25) providing variable speed limited and
hard shoulder running (and RTTI and SRTI) has showed an improvement in
traffic flow over a 12-month period. Vehicle Hours Delay (VHD) has reduced
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considerably in the clockwise direction from 6,736 hours before the scheme was
introduced to 3,750 hours following scheme implementation. The results in the
anticlockwise direction show a reduction from 8,263 VHD to 3,863 VHD which is
a daily saving of 4,400 vehicle hours. Furthermore, the average journey time to
cover this stretch of the M25 improved in both directions. Before the scheme the
clockwise journey time ranged from 15min 56sec to 18min 38sec and after they
ranged from 14min 40 sec to 17min 32sec depending on day and time of day. The
improvement in the clockwise journey time ranges from 5.3% to 8.6%. In the
anticlockwise direction journey time ranged from 16min 3sec to 22min 17sec and
after they ranged from 15min 12 sec to 17min 38sec depending on day and time of
day. The improvement in anti-clockwise journey time ranges from 5.4% to 20.9%
(EU EIP, 2015).
 Another section on the M25 (providing the same services) was also evaluated over
a 12 month period. Vehicle Hours Delay (VHD) has reduced slightly overall in the
clockwise direction from 4,008 hours before the scheme was implemented, to 3,046
hours after the scheme went operational. This is a daily saving of 962 VHD. In the
anti-clockwise direction it has reduced from 3,711 hours prior to scheme
implementation to 2,355 hours after the scheme came into operation. This is a daily
saving of 1,357 VHD. Before the scheme the clockwise journey time ranged from
11min 33sec to 16min 3sec and After they ranged from 11min 30 sec to 15min
20sec depending on day and time of day. The clockwise improvement in journey
time ranges from -0.7% to 10.5%. In the anti-clockwise direction journey time
ranged from 11min 6sec to 15min 10sec and after they ranged from 11min 15 sec
to 13min 2sec depending on day and time of day. The improvement in journey time
ranges from -4.5% to 13.3% (EU EIP, 2017).
From the evaluation of the NEXT-ITS 2 Corridor (EU EIP, 2018), the observed congestion
impacts (in absolute numbers) are a reduction of 491,000 vehicle hours driven and 135,000
vehicle hours spent in congestion per year across the network. This is a result of VMS
providing information on congestion, incidents, accidents and other problems of the
network.
5.8. Bundle 2 – Mobility Management systems
Service Overview
Mobility management systems are somewhat less defined in literature compared to traffic
network management services. In general, mobility management systems services that can
be employed by public bodies to control the flow of users in the mobility system. Public
authorities use multimodal and real-time traffic information to deliver services to end
users, typically in in response to an event or incident (e.g. a rail stop is undergoing
maintenance and replacement bus stop is required). The services are delivered to end-users
via smartphones.
There are limited examples of implementation of such services and therefore no data
available on the impacts under consideration. However, it is expected that the most
significant impact will be increased efficiency of the mobility system and improve travel
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time for individual users. Further, it is possible that it will increase modal shift as it makes
public transport a more reliable and attractive option. It is expected that as data from
operators becomes more widely available to public bodies, mobility management systems
will be rolled out.
5.9. Bundle 3 - Road safety-related minimum universal traffic information
service
Service Overview
Safety-related traffic information (SRTI) services aim to provide road users with useful,
accurate and up-to-date information on events or conditions impacting the road network,
often delivered as alert through smartphones or in-vehicle systems. As defined in
Delegated Regulation 886/2013, the events or conditions covered by are: temporary
slippery road; animal, people, obstacles, debris in the road; unprotected accident area;
short-term road works; reduced visibility; wrong way driver; unmanaged blockage of a
road; exceptional weather conditions.
Impacts
The main objective of providing road safety-related traffic information is increasing road
safety, i.e. reducing road accidents that result in fatalities, injuries and economic loss.
While it is very likely that there is a positive safety impact of SRTI, it is not straightforward
to assess the impact in quantitative terms because the ‘application’ of SRTI is not sharply
defined, limited empirical results exist and other traffic management, traffic control and
cooperative vehicle safety systems target the same safety factors as SRTI. The main data
source for the impacts of SRTI was from the impact assessment study for SRTI (Rapp
Trans et al., 2013) and the evaluation report of the NEXT-ITS Corridor (NEXT-ITS, 2016).
The ex-ante evaluation of the NEXT-ITS Corridor was carried out taking the estimated
benefits of the measures (RTTI and SRTI) into account. The expected impacts of the
deployed services on the NEXT-ITS corridor are based on experience from several impact
assessment studies. The share of users who are provided with the services has been
investigated, based on relevant and available user statistics from each country.
Congestion/Travel Time
The primary effect of safety related traffic information is expected to be safety and as a
result of the reduced number of accidents, the congestion and travel time is expected to
improve. From the ex-ante evaluation of the NEXT-ITS corridor (NEXT-ITS, 2016), the
average effect of safety related traffic information on users on equipped sections was 0.5%
reduction in vehicle hours driven and 1.5% reduction in vehicle hours in congestion. The
The Impact Assessment Study for SRTI assessed the effectiveness, coverage of service
and addressed fraction of all accidents to determine the theoretical safety impacts of SRTI.
The overall safety impact was determined on the basis of the following assumptions: full
coverage of the road network; resolution and accuracy in time and location can be expected
to come from cooperative technology; a near 100% penetration of the service; no other
measures are considered to influence the safety.
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median value (1%) has been taken and an average speed increase was calculated to be
1.01%, which has been applied to cars and trucks across all road types in the absence of
any further data.
Fuel Consumption
Although the primary effect of SRTI is expected to be safety, fuel consumption benefits
will be realised as vehicles change their travel behaviour and route to avoid events and
conditions. From the ex-ante evaluation of the NEXT-ITS corridor the average effect of
safety related traffic information on users on equipped sections was a 0.4% reduction in
CO2 emissions (NEXT-ITS, 2016). This impact has been applied to cars and trucks across
all motorways. For interurban roads, the impact has been scaled in line with the impacts
observed for V2I services, while for urban roads the impact has been assumed to be zero.
Emissions
No data was identified for this impact category in the reports reviewed, therefore emissions
impacts were scaled using the ratio between fuel/CO2 impacts and emissions impacts for
the in-vehicle speed limit service in urban areas (see section 5.13.2). This resulted in the
following impacts on emissions:
 NOx: 0.09% reduction on motorways, 0.09% reduction on other interurban roads
 PM: 0.07% reduction on motorways, 0.1% reduction on other interurban roads
 CO: 0.03% reduction on motorways, 0.05% reduction on other interurban roads
 VOCs: Not included as an impact due to in-vehicle speed limits resulting in an
increase of VOC’s as a consequence of increased braking. The same logic does not
apply to travel information services and therefore the same ratio between fuel/CO2
impacts and emissions cannot be applied.
Safety
The direct effect of SRTI is on driver behaviour. SRTI has a main effect on drivers and
passengers of cars, buses and lorries. Drivers of motorcycles will also be positively
affected by SRTI. Friction-related warnings are especially relevant to motorcyclists and
are likely to have a greater effect as such conditions induce a greater accident risk for
motorcycles. On the other hand, there are some constraints to deliver SRTI to motorcycles
which are likely to lead to a much lower penetration than for passenger cars, at least on the
short and medium term. However, motorcyclists will profit from behaviour more adapted
to local danger by car drivers as a result of SRTI.
The EC impact assessment study for safety related traffic information estimated safety
related traffic information to maximally reduce all road traffic fatalities in Europe by 2.7
% and all traffic injuries by 1.8 %, taking into consideration the assumptions described
above (excluding the cooperative technology approach on the requirement on resolution
and accuracy) (Rapp Trans et al., 2013).
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However, impacts may vary depending on the geographic location of the road. From the
ex-ante evaluation of the NEXT-ITS corridor, the average effect of safety related traffic
information on users on equipped sections was 3% reduction in fatal and injury accidents
(NEXT-ITS, 2016). The evaluation noted that the effects are likely higher due to different
weather conditions. As such, the impact on motorways (both TEN-T and other) was taken
to be 2.7% reduction in fatalities and 1.8% reduction in injuries for all vehicle types to
represent the impact for all EU Member States. For interurban and urban roads, the impacts
have been scaled in line with impacts observed for V2V, which has similar use cases to
SRTI.
Modal Shift
The primary effect of safety related traffic information is expected to be safety; hence the
modal shift impacts are expected to be minimal. No modal shift impacts are therefore
anticipated on an EU level as a consequence of this service and it is not included as part of
the model.
5.10. Bundle 3 - Safe and secure truck parking location information system
Service Overview
This service aims to provide truck drivers with accurate and up to date information on the
location and description of safe and secure truck parking facilities. The service provides
static data to truck drivers including name and address of truck parking area, location
information, number of parking spaces, price and currency of parking and description of
the security, safety and service equipment in the parking area. The primary objective is to
address the number of trucks parked in non-secured zones or unsafe locations like hard
shoulders as a result of lack of information on available parking, which often leaves truck
drivers subject to theft and accidents.
The Delegated Regulation 885/2013 establishes the specifications necessary to ensure
compatibility, interoperability and continuity for the deployment and operational use of
information services for safe and secure parking places for trucks and commercial vehicles
on a Union level in accordance with Directive 2010/40/EU.
Impacts
The purpose of safe and secure truck parking location information systems is to prevent
trucks from parking on the hard shoulder and to help drivers comply with driving time
legislation in a safe way. At the same time, minor impacts on the travel time are expected
as a result of truck drivers reducing the time taken to locate safe parking spaces. Although
it is widely accepted that safe and secure truck parking location information systems will
have positive impact on safety (i.e. a reduction in the number of accidents), there is limited
empirical evidence on the extent of such safety impacts.
The main data source for the impacts on safe and secure truck parking location information
systems was from the evaluation report of the intelligent truck parking system on the
CROCODILE corridor (EU EIP, 2020). By November 2019, resulting from the
development carried out in multiple phases of the project, the number of parking places
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covered by the ITP system had reached 531 in Hungary, covering more than one third of
the public heavy goods vehicle (HGV) parking places available along the TEN-T network.
As a result of the development, rest stations covered by intelligent truck parking-control
system are now available along the motorways in Hungary at nearly every 100 km.
Variable signs posted along the road represent the primary sources of information during
a journey. The LED displays integrated into static signs are identical to those devices used
during the previous deployments for displaying occupancy data of the rest stations. The
incoming information from the new sites are displayed either on new dynamic display units
of static signs deployed earlier, on existing or on newly deployed VMS portals. In addition
to roadside displays, the service has become available on web-based and mobile interfaces
as well, making it easier to access the dynamic occupancy monitoring data of rest areas for
HGVs. The evaluation of ITP system aimed to address whether the number of truck-related
accidents had decreased on the M1 (71% of HGV parking places are covered by the ITP
system) and if so, what the extent of the change is.
Congestion/Travel Time
From the evaluation of intelligent truck parking on the CROCODILE corridor, no direct
relationship could be identified between the expansion of intelligent truck parking services
and changes in traffic flow. However, the evaluation notes that providing information
about safe parking may indirectly have a positive impact the flow of traffic through a drop
in the number of accidents. By decreasing the number of accidents caused by fatigue,
excessive driving, parking at prohibited locations may reduce traffic disturbances (e.g.
congestions or diversions), contributing to an uninterrupted traffic flow and preventing
further, secondary accidents.
Fuel Consumption
The primary effect of safe and secure truck parking location information system is
expected to be safety and travel time; hence the fuel consumption impacts are expected to
be minimal. No fuel consumption impacts are therefore anticipated service and it is not
included as part of the model. This is confirmed by the CROCODILE evaluation report,
which did not consider the effect on fuel consumption for this service.
Emissions
The primary effect of safe and secure truck parking location information system is
expected to be safety and travel time; hence the emissions impacts are expected to be
minimal. No emissions impacts are therefore anticipated on an EU level as a consequence
of this service and it is not included as part of the model. This is confirmed by the
CROCODILE evaluation report, which did not consider the effect on emissions for this
service.
Safety
As highlighted earlier, the primary objective of this service is to prevent trucks from
parking on the hard shoulder and to help drivers comply with driving time legislation in a
safe way thereby reducing the number of accidents involving trucks. In the evaluation
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report of ITP on the CROCODILE corridor, the accident-related data relevant to motorway
M1 was recorded and adjusted to account for increased traffic flow. The number of truck
accidents recorded between 2016-2018 showed an annual decrease in absolute terms
constituting a decrease of 3.9%. At the same time, it is not possible to directly attribute the
safety observed to truck parking as other factors may be involved. The study on
information and reservation truck parking services determined that only 1% of trucks are
related to offsite parking. Thus, as a more conservative figure, 2% was used to reflect the
findings of both studies. This applies only to trucks on motorways.
Modal Shift
The primary effect of safe and secure truck parking location information system is
expected to be safety and travel time; hence the modal shift impacts are expected to be
minimal. No modal shift impacts are therefore anticipated, and it is not included as part of
the model. This is confirmed by the CROCODILE evaluation report, which did not
consider the effect on modal shift for this service.
5.11. Bundle 3 - Safe and secure truck parking location reservation system
This service builds on the location information system and can be viewed as an extension
of the previous service. In addition to providing end users with the static location
information, it provides truck drivers with a convenience service to reserve parking spaces
such that they are able to comply with driving time legislation easily. This service employs
dynamic data as well as static data, including the capacity of the parking facility at any
given moment. This necessitates the appropriate sensor and camera deployment to ensure
that the capacity of the parking facility is monitored continuously.
Regarding specifications for priority action (f) on the provision of reservation services for
safe and secure parking places for trucks and commercial vehicles, the Commission
conducted several consultations with Member State experts and the main stakeholders,
including an impact assessment support study (Rapp-Trans et al., 2012). The discussions
highlighted that there is a low number of parking areas that could offer reservation services
in 2014 (representing only 2% of parking places), and that there was, therefore, no need
for specifications and standards on reservation of parking areas.
Impacts
In addition to the impact of safety discussed above in the previous service type, the main
objective of reservation services is to provide end users with convenience and certainty
that they will be able to use a parking facility at any given moment.
Congestion/Travel Time
As with the location system, the reservation system may have an indirect impact on the
traffic flow as a result of the positive impact on safety. Nevertheless, the impact is
estimated to be small and therefore is not considered in the model.
Fuel Consumption
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The primary effect of safe and secure truck parking location reservation system is expected
to be safety and travel time; hence the fuel consumption impacts are expected to be
minimal. No fuel consumption impacts are therefore anticipated on an EU level as a
consequence of this service and it is not included as part of the model.
Emissions
The primary effect of safe and secure truck parking location reservation system is expected
to be safety and travel time; hence the emissions impacts are expected to be minimal. No
emissions impacts are therefore anticipated on an EU level as a consequence of this service
and it is not included as part of the model.
Safety
Given the limited deployment of truck reservation services and studies on this service type,
no literature that discusses the impact was identified. In the absence of data, the same
impact as the location information services was assumed, which is a 2% reduction in all
safety categories for trucks on motorways.
Modal Shift
The primary effect of safe and secure truck parking location reservation system is expected
to be safety and travel time; hence the modal shift impacts are expected to be minimal. No
modal shift impacts are therefore anticipated on an EU level as a consequence of this
service and it is not included as part of the model.
5.12. Bundle 4 – Vehicle-to-Vehicle (V2V) C-ITS services
The impact data presented in this section are from the 2019 C-ITS impact assessment
support study, which reviewed and updated the information that was collected for the 2016
C-ITS deployment study. The services in Bundle 4 cover day 1 vehicle-to vehicle C-ITS
services, that Emergency electronic brake light (EBL), Emergency vehicle approaching
(EVA), Slow or stationary vehicle(s) warning (SSV), Traffic jam ahead warning (TJW),
and Hazardous location notification (HLN). The General Safety Regulation (GSR) defines
safety technologies and design features that need to be installed in new vehicles in order
to be sold in the EU market. Although the GSR includes several safety designs features
that do not require vehicle connectivity (i.e. direct vision requirements for HDVs), there
are some features such as Intelligent Speed Assistance, for which manufacturers may use
C-ITS type services to adhere to requirements. GSR can therefore be considered closely
linked to C-ITS and certainly complimentary. Based on modelling outputs from the GSR
support study, the benefits of C-ITS services on safety are reduced by 10 percent across
all C-ITS services in the baseline and policy options, which is in line with the 2019 C-ITS
IA support study (Ricardo, 2019). This reduction will more than account for any overlaps
between the effect of C-ITS services on safety and those of the RISM/GSR Regulations160
.
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Other impacts are not reduced in the same way, as these are not quantified in the support study produced
for the GSR Regulation.
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5.12.1. Emergency electronic brake light (EBL)
Service Overview
The emergency electronic brake light is a service aimed at preventing rear end collisions
by informing drivers of hard braking by vehicles ahead. Using this information, drivers
will be better prepared for slow traffic ahead and will be able to adjust their speed
accordingly.
In response to a vehicle suddenly braking, a message is sent to following vehicles to warn
drivers of an abrupt decrease in traffic speed ahead. Emergency electronic brake lights are
displayed in the following vehicles, giving drivers the opportunity to adjust their speed to
avoid a potential collision. This service is applicable on all road and vehicle types, although
it is envisaged to be particularly useful on congested, high speed roads, or in areas where
visibility is poor. In this situation, following vehicles may not be able to see the brake
lights of all vehicles ahead of them and would therefore have very limited time to react to
hard braking without the service. This service currently predominantly relies on V2V ITS-
G5 communication, although a number of projects are looking to demonstrate its
effectiveness using high-speed (e.g. 4G/5G) cellular networks.
Impacts
The main data source for the impacts of the emergency electronic brake light was from
FOTs in the DRIVE C2X project (TNO, 2014), an overview of the general methodology
is provided in Table 46. This service was only tested in Germany, in partnership with the
simTD
project (Schimandl et al., 2013). A US DoT cost-benefit analysis report was also
used as a comparison.
Table 46: Overview of key data source – DRIVE C2X project
The DRIVE C2X project used log data resulting from Field Operational Tests (FOTs)
carried out on several test sites in different EU countries (Finland, France, Germany,
Italy, the Netherlands, Spain, and Sweden).
The study aimed to harmonise the testing conditions as far as possible, in order to allow
the data across the pilot sites to be combined. Nevertheless, several aspects differed
significantly from one test site to others. These differences can be explained by cultural,
country specific aspects as well as acquisition related influences (private drivers vs.
employees).
The FOTs focused on functions that provide information or warnings to drivers. This
means that the impact is dependent on whether and how the driver responds. Thus, the
impact assessment first aimed to measure driver behaviour in order to provide input data
for an impact assessment in four target areas: safety, efficiency, mobility, and
environment.
Driver behaviour data was collected in two main ways: controlled tests” (CTs) and
naturalistic driving (ND). In CT, drivers were called into the test and followed the
driving instructions provided by the Test-Site Instructor, allowing the driver to
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encounter specific test situations. In the ND approach, drivers were monitored in their
daily driving. Data on driver behaviour was then pooled across the test sites and used as
input for the assessment of impacts.
Safety impacts were calculated by making use of the results of the field tests regarding
driver behaviour, expert assessment and previous expert assessments found in the
literature. Traffic efficiency and environmental impact assessment made use of
simulation models. The mobility impact assessment in DRIVE C2X was based on the
mobility model developed in TeleFOT project, The mobility assessment data consisted
of user interviews (questionnaires and focus groups) based on experience in real traffic.
The scaling up of the effects to the EU-level made use of external data.
Source: (TNO, 2014)
Other studies that considered the impacts include the eIMPACT project (TNO, VTT,
Movea, PTV, BASt, 2008), and a cost-benefit analysis performed for the U.S. Department
of Transport. The DRIVE C2X data was prioritised ahead of these source as it was
published in 2014 (compared to 2008 for the other sources), is based on FOT data and its
primary focus is on the EU, compared to the US DoT study.
Traffic efficiency
The primary effect of emergency electronic brake light is intended to be on safety, hence
the traffic efficiency impacts are expected to be minimal. No traffic efficiency effects are
therefore anticipated on an EU level as a consequence of this service and it is not included
as part of the model. This is confirmed by the DRIVE C2X study, which did not consider
traffic efficiency effects for this service.
Fuel consumption and CO2
The primary effect of emergency electronic brake light is intended to be on safety, hence
the fuel efficiency impacts are expected to be minimal. No fuel efficiency benefits are
therefore anticipated on an EU level as a consequence of this service and it is not included
as part of the model. This is confirmed by the DRIVE C2X study, which did not consider
the effect on fuel consumption for this service.
Environmental and emissions impacts
The primary effect of emergency electronic brake light is intended to be on safety, hence
the emissions impacts are expected to be minimal. No effects on emissions are therefore
anticipated on an EU level as a consequence of this service and it is not included as part of
the model. This is confirmed by the DRIVE C2X study, which did not consider the effect
on polluting emissions for this service.
Safety
The primary objective of this service is to prevent rear end collisions, although other types
of accident may also be prevented. Specifically, this service is thought to reduce the
number of panic manoeuvres performed by vehicles, due to the early warning. This service
can act via two mechanisms (TNO, 2014):
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 Direct in-vehicle modification of the driver task – the driver behind the braking
vehicle has more time to react to the braking vehicle ahead.
 Modification of interaction between vehicles – following drivers (with or without
emergency brake light capability) will also have more time to react to the braking
vehicle ahead.
In the DRIVE C2X study, impacts were assessed separately for: a) motorways and high
speed rural roads (with a speed limit of at least 80 km/hour) and b) urban roads and low
speed rural roads. The assumptions made in the DRIVE C2X study in scaling up these
impacts are detailed below (TNO, 2014).
Rear-end collisions prevented via direct in-vehicle modification of the driving task:
 60-80% of fatalities and injuries on rural roads occur on high speed rural roads,
whilst all fatalities and injuries on motorways are considered to be high-speed
(>80km/h).
 It is assumed that 50-70% of rear end collisions occurring on motorways and high
speed rural roads could be influenced by the emergency brake light service.
o 20-30% of these fatalities and injuries could be prevented by the emergency
electronic brake light.
 It is assumed that 10-25% of rear end collisions occurring on urban roads and low
speed rural roads (the remaining 20-40% of rural roads) could be influenced by the
emergency brake light service.
o 30-40% of these fatalities and injuries could be prevented by the emergency
electronic brake light.
Other collision types (other than rear-end) prevented via direct in-vehicle modification of
the driving task:
 Magnitude of the safety benefit was estimated to be 5-10% of the impact for rear
collisions (as described above) per accident type.
Rear-end collisions prevented via modification of interaction between road users:
 When a driver reacts to hard braking ahead, following vehicles will also have
increased time to react.
o On motorways and high speed rural roads, a 0.10-0.15% reduction in
fatalities is expected.
o On motorways and high speed rural roads, a 0.02-0.03% reduction in
injuries is expected.
o On urban roads and low speed rural roads, a 0.15-0.30% reduction in
fatalities is expected.
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o On urban roads and low speed rural roads, a 0.10-0.20% reduction in
injuries is expected.
The relatively low effectiveness of this service for interactions between road users is due
to the high element of surprise and very small time margins involved in these types of
crashes.
Overall for the EU-28, the DRIVE C2X study calculated a decrease in fatalities between
25 and 304 in 2030 and a decrease in injuries between 1,322 and 16,219 in 2030.
The DRIVE C2X high penetration scenario was used as an input to the model, which
corresponds to a 2.7% decrease in fatalities and a 2.5% decrease in injuries.
The US DoT also assessed the potential safety impact of this service in 2030 as part of a
cost-benefit analysis and calculated a 0.88% decrease in annual light vehicle crashes,
which is a significantly lower figure than DRIVE C2X. The discrepancy is likely to be due
to the differences in road and driving characteristics in the USA and EU and higher traffic
density on European roads.
Other impacts
As part of DRIVE C2X, user acceptance tests were not carried out for the emergency brake
light functionality. The simTD
project reported that driver behaviour was not significantly
affected by the emergency brake light, although recommends further studies to support
this. The simTD
project questions whether there are benefits for drivers further behind the
braking vehicle and again proposes that further research should be carried out to determine
the impact of this service on all vehicles in a queue.
5.12.2. Emergency vehicle approaching (EVA)
Service Overview
This service aims to give an early warning of approaching emergency vehicles, prior to the
siren or light bar being audible or visible. This should allow vehicles extra time to clear
the road for emergency vehicles and help to reduce the number of unsafe manoeuvres.
Approaching emergency vehicles will communicate with vehicles ahead to warn drivers
to clear the road. The advance warning provided by this service will give vehicles extra
time to clear the road for approaching emergency vehicles in a safe and timely manner.
This service is applicable for all road and vehicle types. This service currently
predominantly relies on V2V direct short-range communication, although a number of
projects are looking to demonstrate its effectiveness using high-speed (e.g. 4G/5G) cellular
networks.
Impacts
The main data source for the impacts of the emergency vehicle approaching service was
the DRIVE C2X project (TNO, 2014). An overview of the general methodology is
provided in Table 46. Trials of this service were carried out at test sites in Germany, Italy
and Spain. Data for this service was very limited, perhaps due to the limited real world
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opportunities to trial this type of service. No other publicly available studies that examine
the emergency vehicle approaching service specifically were identified.
Traffic efficiency
The primary effect of the emergency vehicle approaching service is intended to be on
safety, hence the traffic efficiency impacts are expected to be minimal. No traffic
efficiency effects are therefore anticipated on an EU level as a consequence of this service
and it is not included as part of the model. This is confirmed by the DRIVE C2X study,
which did not consider traffic efficiency effects for this service.
Fuel consumption and CO2
The primary effect of the emergency vehicle approaching service is intended to be on
safety, hence the fuel efficiency impacts are expected to be minimal. No fuel efficiency
benefits are therefore anticipated on an EU level as a consequence of this service and it is
not included as part of the model. This is confirmed by the DRIVE C2X study, which did
not consider the effect on fuel consumption for this service.
Environmental and emissions impacts
The primary effect of the emergency vehicle approaching service is intended to be on
safety, hence the emissions impacts are expected to be minimal. No effects on emissions
are therefore anticipated on an EU level as a consequence of this service and it is not
included as part of the model. This is confirmed by the DRIVE C2X study, which did not
consider the effect on polluting emissions for this service.
Safety
A reduction in collisions can be expected when this service is implemented due to the
increased time drivers have available to inform their driving decisions.
The DRIVE C2X study used French accident statistics to estimate the impact of the
emergency vehicle approaching warning (TNO, 2014), which show that 0.8% of fatal
accidents and 1.1% of injuries included an emergency vehicle. This does not include
accidents where the emergency vehicle was not directly involved. A multiplier of 1-5 was
used for these accidents. Of these additional accidents, it was estimated that only 1-5%
would result in injuries or fatalities.
The accidents were then categorised according to whether they occurred at an intersection
or on a link section of road. Here, the following assumptions were made:
 50-70% of emergency vehicle related (directly or indirectly) fatalities and injuries
occur at intersections (Auerbach, 1988).
 50-70% of emergency vehicle related (directly or indirectly) fatalities and injuries
occurring at intersections could be prevented by the emergency vehicle
approaching service.
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 60-80% of emergency vehicle related (directly or indirectly) fatalities and injuries
occurring at links (the remaining 30-50% of total fatalities and injuries) could be
prevented by the emergency vehicle approaching service. This higher figure is due
to the lower complexity of the road layout and reflects the fact that it is likely to be
easier for drivers to give way to emergency vehicles.
The results in the DRIVE C2X report were presented in terms of the overall impact in the
EU-28 in 2030. It was estimated that 14-84 fatalities and 933-4954 injuries could be
prevented (TNO, 2014). The high scenario in DRIVE C2X equates to a 0.8% reduction
in fatalities and a 0.8% reduction in injuries.
Other impacts
A survey of test participants during the DRIVE C2X study revealed some interesting
insights regarding this service. 92% of participants viewed the service as useful (the
highest in the study), however only 41% indicated they would be willing to pay for this
feature (TNO, 2014). On a scale of 1 to 7, the average increased feeling of safety was rated
at 5.6-6.0, suggesting that this service can offer an improved driving experience.
5.12.3. Slow or stationary vehicle(s) warning (SSV)
Service Overview
Slow or stationary vehicle(s) warning is intended to deliver safety benefits by warning
approaching drivers about slow or stationary/broken down vehicle(s) ahead, which may be
acting as obstacles in the road. The warning helps to prevent dangerous manoeuvres as
drivers will have more time to prepare for the hazard. This service can also be referred to
as car breakdown warning.
Slow or stationary vehicle(s) signal to nearby vehicles to warn approaching drivers of their
presence. These messages can then be relayed to following drivers, who can consequently
plan to take an alternative route, or make evasive manoeuvres, thus improving traffic
fluidity, safety and delivering efficiency benefits. This service is applicable to all road and
vehicle types. As for the emergency electronic brake light service, it is anticipated that this
service will be especially useful for warning vehicles of the potential danger of a rear end
collision when visibility is poor. This service currently predominantly relies on V2V direct
short-range communication, although a number of projects are looking to demonstrate its
effectiveness using high-speed (e.g. 4G/5G) cellular networks.
Impacts
The main data source for the impacts of slow or stationary vehicle(s) warning was the
DRIVE C2X project (TNO, 2014). An overview of the general methodology is provided
in Table 46. This service was tested at sites in Finland, Italy, Spain and Sweden. In DRIVE
C2X, this service is evaluated alongside ‘obstacle warning’ and ‘roadworks warning’, as
the services perform a similar function, act via similar mechanisms and present information
to drivers in a similar manner.
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The eIMPACT project (TNO, VTT, Movea, PTV, BASt, 2008) evaluated the impacts of a
service called ‘wireless local danger warning’, which is based on V2V communication. An
overview of the general methodology is provided in Table 47. The eIMPACT definition
of this service includes both obstacle/stationary vehicle warning and weather warning
functionality.
Table 47: Overview of key data source – eIMPACT project
The eIMPACT project assessed the socio-economic effects of Intelligent Vehicle Safety
Systems (IVSS) and their impacts on safety and traffic efficiency. Results from the impact
assessment (Deliverable D4) were then used to inform a cost-benefit analysis (Deliverable
D6).
The results of the study were published in 2008 and calculated the potential impacts of IVSS
in the years 2010 and 2020. The impact assessment was performed for low (business as
usual) and high (policy incentives) scenarios for both years. For each scenario, the fleet
penetration varied by service, vehicle type (passenger car or goods vehicle) and by year
(2010 or 2020). In addition to the scenarios, the maximum effectiveness of each service
based on 100% penetration at EU-25 level was also calculated as part of eIMPACT. Results
were given for the EU-25 as a whole and are not separated by road type, or vehicle type.
Values based on 100% penetration were used as a source of data in this project.
Twelve services were evaluated, although only three were defined as having cooperative
functionality:
 Intersection safety - the description of this service in the eIMPACT report also includes
GLOSA/TTG functionality and is not limited to signalised intersections (also provides
right of way assistance and left turn assistance).
 Speed alert - considers the service to have V2I functionality in 2020 but not in 2010.
 Wireless local danger warning - includes weather warnings and obstacle/stationary
vehicle warnings, both of which are based on V2V communication.
Another service, pre-crash protection of vulnerable road users, was also evaluated. This is
similar to the vulnerable road user protection service evaluated in this IA, however in
eIMPACT it was not considered to be a cooperative system and was assumed to operate by
detecting vulnerable road users via sensors. The two services are likely to present
information to the driver in a similar manner and safety impacts will occur via similar
mechanisms, therefore the data presented can reasonably be believed to be of some value.
Safety impacts were calculated by making use of expert estimations and were scaled up to
EU-25 level based on current accident statistics. In addition to this, consultation with key
stakeholders was an integral part of the eIMPACT project.
Source: (TNO, VTT, Movea, PTV, BASt, 2008)
Traffic efficiency
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The traffic efficiency impacts of the slow or stationary vehicle(s) service are expected to
be minimal as its purpose is to improve safety, rather than prevent traffic jams (TNO, VTT,
Movea, PTV, BASt, 2008). In addition to this, broken down, stationary, or exceptionally
slow vehicles (such as tractors) on the road are relatively infrequent events, therefore
effects on traffic on an EU level will be negligible. This impact is therefore not included
in the model.
Fuel consumption and CO2
The primary effect of the slow or stationary vehicle warning is intended to be on safety,
hence the fuel efficiency impacts are expected to be minimal. No fuel efficiency benefits
are therefore anticipated on an EU level as a consequence of this service and it is not
included as part of the model. This is confirmed by the DRIVE C2X study, which did not
consider the effect on fuel consumption for this service.
Environmental and emissions impacts
The primary effect of the slow or stationary vehicle warning is intended to be on safety,
hence the emissions impacts are expected to be minimal. No effects on emissions are
therefore anticipated on an EU level as a consequence of this service and it is not included
as part of the model. This is confirmed by the DRIVE C2X study, which did not consider
the effect on polluting emissions for this service.
Safety
This service is expected to work by informing drivers of slow or stationary vehicle(s)
before they would be aware of the hazard without the service and may be particularly
beneficial if the hazard is in an area with low visibility. This should enable drivers to have
more time to prepare and navigate safely past the slow/stationary vehicle. In the DRIVE
C2X study, a decrease in speed was observed for vehicles participating in the trial.
The DRIVE C2X study used accident statistics for single vehicle accidents with an object
other than a pedestrian for three road types (motorways, rural roads and urban roads) to
scale up the FOT results to EU level. The following assumptions were then made to scale
up the potential safety impacts:
 10-20% of accidents with an object other than a pedestrian the object would be a
broken down vehicle.
 The effectiveness of car breakdown warning would vary depending on road type.
The percentage of accidents prevented by road type is given below.
o Motorways: 70-90%
o Rural roads: 65-85%
o Urban roads: 30-50%
Using these findings, the authors presented data in terms of the number of expected injuries
and fatalities prevented (TNO, 2014). For the year 2030, this has been estimated to be
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between 12-125 fatalities and 427-2794 injuries (figures assume 76% fleet penetration).
The high scenario in DRIVE C2X equates to an average 1.1% decrease in fatalities and
a 0.7% decrease in injuries.
The eIMPACT study also covered this service as part of the wireless location danger
warning (one aspect of which is obstacle/stationary vehicle warning). In total, this service
is estimated to have a 4.5% reduction in fatalities and a 2.8% reduction in injuries. This
estimate assumes 100% penetration and the results are presented for EU-25 level. These
values are much larger than those predicted by DRIVE C2X, however this is likely due to
the fact that in eIMPACT, weather conditions were also considered as part of the wireless
location danger warning service.
To check for agreement between the two sources, the DRIVE C2X safety impacts for slow
or stationary vehicle(s) and weather warning were added together. This gave a total impact
of 4.56% on fatalities and a 4.04% impact on accidents. The impact on fatalities compares
well to eIMPACT data, however the combined impact on injuries for slow or stationary
vehicle and weather warning predicted by DRIVE C2X is larger than that predicted by
eIMPACT.
The DRIVE C2X data has been used in preference to the eIMPACT data for input into the
model, as it is based on FOT data and because it provides a separate impact for slow or
stationary vehicle warning, whereas eIMPACT does not.
Other impacts
User acceptance for the car breakdown, or slow or stationary vehicle warning was one of
the highest observed during the DRIVE C2X project and was widely noted to be a very
helpful feature. Drivers particularly liked the increased feeling of safety gained by reducing
the surprise of encountering a slow, stationary, or broken down vehicle in the road (TNO,
2014).
5.12.4. Traffic jam ahead warning (TJW)
Service Overview
The Traffic Jam Ahead Warning (TJW) provides an alert to the driver on approaching the
tail end of a traffic jam at speed - for example if it is hidden behind a hilltop or curve. This
allows the driver time to react safety to traffic jams before they might otherwise have
noticed them themselves. The primary objective is to avoid rear end collisions that are
caused by traffic jams on highways.
This service is applicable for all road and vehicle types, however its main benefit is
expected to be on high speed roads (TEN-T Corridors, TEN-T Core and TEN-T
Comprehensive network), where the system will be able to warn of traffic ahead faster than
the driver is capable of identifying the danger. This service currently predominantly relies
on V2V direct short-range communication, although a number of projects are looking to
demonstrate its effectiveness using high-speed (e.g. 4G/5G) cellular networks.
Impacts
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The main data source for the impacts of TJW was the DRIVE C2X project (TNO, 2014).
An overview of the general methodology is provided in Table 46.
For TJW, Field tests were carried out at the test sites in Spain, Italy and Germany. The test
site in Germany had such a small number of traffic jams that no impacts were found. Italy
also had a small number of events recorded – since real vehicle queues did not occur at all,
artificial TJW events were triggered manually in high traffic density situations on
motorways. Similarly, the test site in Spain had few traffic jams occurring, mainly in urban
areas. Since the TJW events from Italy and Spain came from two different traffic scenarios
(highway vs. urban roads respectively), it was difficult to draw a conclusion on the
effectiveness from the pooled data. Nevertheless, an assessment was made using the
available information and expert judgement.
In addition to DRIVE C2X, the EasyWay study considered the safety impacts of TJW
(EasyWay, 2012). The EasyWay figures were based on the eIMPACT project from 2008,
which scaled the values up to EU-25 level, therefore the DRIVE C2X data were used in
preference. An overview of the methodology for the EasyWay project is provided in Table
48.
Table 48: Overview of key data source – EasyWay project
The cost-benefit analysis carried out in the EasyWay study considered the impacts of C-
ITS on road safety, efficiency and congestion/traffic efficiency as well as fuel
consumption and emissions. The analysis was carried out for the year 2030 and assumed
100% of all vehicles will be equipped with some form of communication device that can
facilitate cooperative services. The study assumed that one third will be installed by
OEMs, one third will be aftermarket devices and one third will be nomadic devices.
Primary data (for 2010) was obtained from national representatives and usually came from
gathered national statistics, including:
 Vehicle fleet compositions
 Vehicle kilometres driven by road type
 Road accident statistics by severity (i.e., fatalities, injured, property damage etc.)
 Congestion (i.e., delays),
 Emissions (NOx, CO, PM2.5)
 Fuel Economy/CO2 emissions for diesel and petrol cars
 Road infrastructure deployment
In cases where data was missing, the missing data was estimated by
interpolating/extrapolating between countries with similar characteristics (left undefined
by authors), the resulting estimates were then sent for approval form that country's
representatives in the task.
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To make more robust estimates for C-ITS impacts, adaptations were made to account for
changes in driving behaviour and travel behaviour. These adaptations were based on
simple models taken from various literature sources. The key sources were:
 Kulmala, R.; Leviäkangas, P.; Sihvola, N.; Rämä, P.; Francics, J.; Hardman, E.;
Ball, S.; Smith, B.; McCrae, I., Barlow, T.; Stevens, A. (2008). CODIA
Deliverable 5: Final Study Report. CODIA Co-Operative systems Deployment
Impact Assessment. Submitted to European Commission DG-INFSO
 Wilmink I., Janssen W., Jonkers E., Malone K., van Noort M., Klunder G., Rämä
P., Sihvola N., Kulmala R., Schirokoff A., Lind G., Benz T., Peters H. &
Schönebeck S. (2008). Impact assessment of Intelligent Vehicle Safety Systems.
eIMPACT Deliverable D4. Version 1.0 April 2008.
 Janssen W.H., Brouwer R.F.T. and Huang Y. (2004). Risk trade-offs between
driving behaviour and driver state. AIDE Deliverable D2.3.2.
 Nilsson G. (2004). Traffic Safety Dimensions and the Power Model to describe
the effect of speed and safety. Bulletin 221. Department of Technology and
Society. Lund University. Sweden.
The data required to parametrise these models were usually taken from the same papers
that presented the models. For example, for hazardous location notification
 It is assumed that it comprises of low friction warnings and low visibility warning.
The corresponding estimated safety improvements are: 5% and 12% reductions in
injury crashes, respectively; and 10% and 23% reductions in fatal crashes,
respectively [Kulmala et. al. (2008) Nilsson (2004)]
 Following Kulmala et. al. (2008) and Janssen et. al. (2006), the effects of increased
awareness is assumed to further reduce the risk of accidents by 11%
 Kulmala et. al. (2008), utilising the results of Janssen et. al. (2006) estimated an
overall headway-related crash risk decrease of 4%
 Assuming that speed awareness and headway effects are independent (an
assumption that is made for all mechanism and sub-mechanisms in adapting for
behavioural changes) safety impacts for hazardous location notification is -22%
(0.915 x 0.89 x 0.96 = 0.78) for injuries and -29% (0.835 x 0.89 x 0.96 = 0.71) for
fatal accidents/fatalities.
Finally, the forecasts for 2030 were estimated from the 2010 data by utilising any existing
national forecasts and the forecasts provided by the eIMPACT (Wilmink et al. 2008) and
CODIA projects (Kulmala et al. 2008). In addition, the general energy use and CO2
forecast were taken from European Energy and Transport Trends to 2030 (published in
2007)161
. Note that for safety, the 2020 forecast was used for the 2030 forecast because
the authors assumed that almost all additional safety improvement between 2020 and 2030
161
http://ec.europa.eu/dgs/energy_transport/figures/trends_2030_update_2007/energy_transport_trends_2030_update_2007_en.pdf
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would result from cooperative systems. As for the other estimates, all forecasts were
validated by the national representatives.
Source: (EasyWay, 2012).
Traffic efficiency and congestion
In DRIVE C2X, the traffic efficiency impacts of TJW were examined using traffic
simulation, which did not show any statistically significant changes in traffic efficiency
(TNO, 2014). This is because TJW affects how a driver approaches the tail of a traffic jam
and will not affect the duration of the traffic jam. Multiple simulation runs also found that
there were no second order effects impacting the characteristics of an existing traffic jam
(TNO, 2014), and hence this impact was considered insignificant for the purposes of this
study. Therefore, zero impact was assumed for this impact category in the model.
Fuel consumption and CO2
The primary effect of TJW is intended to be on safety. Hence the fuel efficiency impacts
are expected to be minimal. Minor reductions in fuel consumption could occur if a driver
were able to decelerate more economically. Nevertheless, the effects are small and valid
only for a short distance influenced by the traffic jam. The results from DRIVE C2X
confirmed that impacts on fuel efficiency were statistically insignificant and could not be
scaled up to the EU level (TNO, 2014).
Environmental and emissions impacts
The primary effect of TJW is intended to be on safety. Hence the environmental impacts
are expected to be minimal. Minor reductions in pollutant emissions could occur if a driver
were able to decelerate more economically. Nevertheless, the effects are small and valid
only for a short distance influenced by the traffic jam. The results from DRIVE C2X
confirmed that impacts on pollutants were statistically insignificant and could not be scaled
up to the EU level (TNO, 2014).
Safety
The primary safety benefit provided by TJW is to avoid a rear-end collision due to ensuring
earlier driver awareness of a traffic jam tail (TNO, 2014). In case of high traffic flow, there
might be problems of side-by-side collisions and other accident types as well if drivers
carry out panic manoeuvres.
In DRIVE C2X, safety effects were presented for the EU-28 as a percentage reduction in
fatalities or injuries in 2030, corresponding to various scenarios, which are based on a
combination of different fleet penetration levels and the level of ambition of safety impact
estimates.
Specifically, positive effects that were expected are:
 The driver will slow down earlier than without TJW.
 The driver will slow down to a lower speed than without TJW.
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 The driver will not slow down earlier, but be able to react faster on approach to the
traffic jam.
 The driver may also brake more smoothly when reaching the traffic jam, or to keep
the lane in case of high traffic flow.
A possible rebound effect is that the driver would pay less attention to potential traffic jams
due to relying on the system. However, the information provision is dependent on equipped
vehicles being present to send the warning.
When the user of TJW approaches the traffic jam more smoothly, the non-users behind
will most likely do so, too. The amount of fatalities and injuries in rear collisions caused
by traffic jam to be prevented was assessed to be 1-5% for all driving environments due to
smoother non-user driving behaviour. The impact was assessed to be 5-10% of the impact
for rear collisions to other accident types except frontal collisions.
In DRIVE C2X, FOT results were scaled up to EU-28 level based on the number of traffic
jams in the EU-27. This was based on data from the Netherlands, since information for the
EU was not available.
In the DRIVE C2X high scenario, the overall safety impact of TJW was calculated to be
up to 193 prevented fatalities and up to 16,619 prevented injuries per year in the EU-28 in
2030. This is equivalent to a 1.7% reduction in fatalities and a 2.5% reduction in injuries.
The EasyWay project calculated the impact of the traffic jam ahead warning service on
injury and fatal accidents at EU-27 level. The results from this study are shown below:
 Injury accidents and injuries: Average 2.8% reduction in injuries
o (-4.9% on motorways, -4.1% on interurban and rural roads, and -2.0% on
urban roads)
 Fatal accidents and fatalities: Average 2.4% reduction in fatalities
o (-3.3% on motorways, -2.8% on interurban and rural roads, and -1.6% on
urban roads)
These values are higher than those calculated by the DRIVE C2X report (see Table 49),
however the benefits are separated by road type, as desired for the modelling. It was
decided to use the DRIVE C2X data as an input to the model (given the fact that it is based
on FOTs) but the impact was scaled for each road type based on the ratios from the
EasyWay studies. This gave the following safety impacts:
 Motorways: 2.4% reduction in fatalities, 4.4% reduction in injuries
 Other interurban roads: 2.0% reduction in fatalities, 3.7% reduction in injuries
 Urban roads: 1.2% reduction in fatalities, 1.8% reduction in injuries
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Table 49: Summary of safety impacts of the traffic jam ahead warning service stated in various EU studies
Study Fatalities (reduction) Injuries (reduction) Scenario
DRIVE
C2X
1.74% 2.52% 76% penetration, high
safety impact estimate
EU-28, 2030
EasyWay 2.4% (average)
3.3% (motorways)
2.8% (interurban
roads)
1.6% (urban roads)
2.8% (average)
4.9% (motorways)
4.1% (interurban
roads)
2.0% (urban roads)
100% penetration
EU-27, 2030
Other impacts
Subjective assessment carried out in DRIVE C2X using stakeholder input suggested that
TJW could help to achieve very slight decreases in stress and uncertainty, and contribute
to slightly increased feelings of safety and comfort (TNO, 2014). The scores provided on
a rating scale however fell close to the middle (i.e. a neutral impact) and therefore the
effects are considered in this IA to be insignificant overall. User acceptance was relatively
high, with 79% of the respondents in the DRIVE C2X survey willing to use the function
(TNO, 2014).
There were no indications of any impact on modal shift (TNO, 2014).
5.12.5. Hazardous location notification (HLN)
Service Overview
This service gives drivers an advance warning of upcoming hazardous locations in the
road. Examples of these hazards include a sharp bend in the road, steep hill, pothole,
obstacle, or slippery road service. Using this information, drivers will be better prepared
for upcoming hazards and will be able to adjust their speed accordingly.
Hazardous locations are automatically detected by vehicles in response to changing driving
behaviour or information gained from vehicle information systems. For example, a sharp
bend may be detected by rapid braking and change of vehicle direction, while a pothole
may be detected by a vehicle’s electronic stability control system. Information concerning
the specific location and type of danger is retained and sent to vehicles in the surrounding
area, warning of the hazard. This service is suitable for all vehicles and road types and may
be used in combination with data gained from V2I services such as weather warning and
in-vehicle signage. Whilst it is expected to rely primarily on V2V ITS-G5 communication,
a number of projects are looking to demonstrate its effectiveness using high-speed (e.g.
4G/5G) cellular networks.
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Impact data
The main data sources for the impacts of the hazardous location notification service are
the EasyWay, eIMPACT, CODIA, NordicWay Coop and eSafetyForum Intelligent
Infrastructure Working Group reports. The EasyWay and CODIA projects uses estimates
from eIMPACT. An overview of the general methodology for the eSafetyForum Intelligent
Infrastructure Working Group Report is provided in Table 51, while an overview of
CODIA is provided in Table 50.
Table 50: Overview of key data source - CODIA
The CODIA study (Co-Operative Systems Deployment Impact Assessment) aimed to
evaluate the costs, impacts and benefits of five C-ITS services, namely:
 Speed adaptation due to weather conditions, obstacles or congestion (V2I)
 Reversible lanes due to traffic flow (V2I)
 Local danger / hazard warning (V2V)
 Post-crash warning (V2V)
 Cooperative intersection collision warning (V2V and V2I)
The potential impacts of the selected C-ITS services were assessed up to the year 2030 and
considered the entire vehicle fleet in EU-25 countries. Data was obtained from a wide range
of literature sources including scientific journals, relevant EU R&D projects (in particular
the COOPERS, CVIS and SAFESPOT projects) and the US DoT, For the impact
assessment. The majority of vehicle, accident and traffic data was obtained from the
eIMPACT project.
As many systems were not fully defined while the study was being carried out, assumptions
and key findings were validated with experts from the European Commission, related
European research projects, industry, and academia.
Source: (VTT, TRL, 2008)
Table 51: Overview of key data source - eSafetyForum Intelligent Infrastructure Working Group Final
Report
The eSafetyForum Intelligent Infrastructure Working Group (II WG) was formed to define
Intelligent Infrastructure. The II WG aimed to answer five key questions, which are
addressed in the Final Report:
What is intelligent infrastructure?
Which services contribute to the implementation of Intelligent Infrastructure?
Which technological resources are necessary for these services and which business areas
need to implement them?
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What needs to be done to assist/promote the implementation of these technological
resources and services?
What is the relation between Intelligent Infrastructure and Intelligent Vehicles?
As part of this report, a literature review, surveying over 20 papers was performed to assess
the potential benefits and added value for a number of C-ITS services. Data for three impact
categories (impact on fatalities/injuries, impact on congestion, impact on CO2 emissions)
were gathered for a variety of services. Services covered which are relevant to this study
are: real time event information, real time traffic information, travel time information,
weather information, speed limit information, parking information and guidance, local
hazard warning, dynamic route guidance, emergency vehicle warning, wrong way driving
warning, road user charging, requesting green/signal priorities, and intelligent truck
parking.
The final report mentions a number of limitations of the values presented, noting that
“figures are all based on detailed specifications of the system in question” and that “similar
systems with a different technology set-up or different content quality may have largely
deviating estimates of effectiveness with regard to safety, efficiency, mobility and
environment”. The report stresses that local effects will be vastly different to EU scale
impacts, although does not state whether the results presented are for single events, or for
EU level. Further to this, penetration rates are not given for the impact data and results are
not broken down by vehicle type, road type, or accident type (in the case of safety impacts).
At the time of publication (2010), few evaluation studies for cooperative systems had been
performed and furthermore, the authors stated that very few quantitative estimates of the
impacts have been produced. As a result, data from this study was treated with caution and
was only used in the absence of any other data.
Traffic efficiency
The eSafetyForum Intelligent Infrastructure Working Group Final Report found a 2-10%
reduction in congestion. The report does not specify penetration level, vehicle type or road
type (eSafetyForum, 2010). Further to this, it is unclear whether this is the impact of a
single event, or whether the results were scaled up to EU level (as discussed in Table 51).
The lower end of this range was therefore assumed, i.e. an impact of 2% improvement in
speed across all vehicle types on urban roads.
Fuel consumption and CO2
No data was identified for this impact category in the reports reviewed. The primary effect
of the hazardous location service is intended to be on safety, hence the fuel efficiency
impacts are expected to be minimal. No fuel efficiency benefits are therefore anticipated
on an EU level as a consequence of this service and it is not included as part of the model.
Environmental and emissions impacts
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No data was identified for this impact category in the reports reviewed. The primary effect
of the hazardous location service is intended to be on safety, hence the emissions impacts
are expected to be minimal. No emissions benefits are therefore anticipated on an EU level
as a consequence of this service and it is not included as part of the model.
Safety
The safety impacts of this service were covered by several papers. The EasyWay study
calculated the impact of the hazardous location service on injuries and fatalities by taking
into consideration the expected change in vehicle speed (as discussed in Table 48). The
impacts were also calculated by road type, therefore this data is used in preference to those
given by the eSafetyForum Intelligent Infrastructure Working Group Final Report and the
CODIA study. However, correspondence with a project representative from the
NordicWay Coop project suggested that the values are lower, as displayed in Table 52. A
30% reduction has therefore been applied to the CODIA study impact values to take
into account the new NordicWay data.
The impact on injuries and accidents calculated by EasyWay (and now scaled down by
30%) were used in the model as they build on the CODIA study and are broken down by
road type. The impacts are as follows:
 Injury accidents and injuries: Average 3.1% reduction
o This is equivalent to -3.7% on motorways, -3.7% on interurban and
rural roads, and -1.3% on urban roads
 Fatal accidents and fatalities: Average 4.1% reduction
o This is equivalent to -3.6% on motorways, -3.7% on interurban and
rural roads, and -1.2% on urban roads
The eSafetyForum report (eSafetyForum, 2010) gives a value of 2-10% for the estimated
reduction in fatalities/injuries. Assuming the average of this range is taken (6%), this value
is significantly larger than the averages reported by EasyWay. The objective of the
eSafetyForum report was to given an indication of the possible benefits, therefore the range
is likely to capture all estimates, regardless of whether some data points may be outliers.
The CODIA report (VTT, TRL, 2008) also assessed the impact of local danger warnings.
At 100% penetration, the authors state that a 4.2% reduction in fatalities and a 3.1%
reduction in injuries is expected, provided that the system is used for all vehicle kilometres
driven.
Table 52: Summary of safety impacts for the hazardous location service, as reported in EU C-ITS studies
Study Fatalities
(reduction)
Injuries (reduction) Scenario
EasyWay 4.1% (average)
5.2% (motorways)
3.1% (average)
5.3% (motorways)
100% penetration
EU-27, 2030
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Study Fatalities
(reduction)
Injuries (reduction) Scenario
5.3% (interurban
and rural roads)
1.7% (urban roads)
5.3% (interurban and
rural roads)
1.9% (urban roads)
eSafetyForum 2-10% 2-10% Not stated
CODIA 4.2% 3.1% 100% penetration,
expected impact if all
vehicles were equipped,
regardless of year
NordicWay 2.1% 2.5% 31-65% traffic flow
penetration (all main
roads)
Finland, 2030
Other impacts
No data related to other impacts was identified in the reports reviewed.
5.13. Bundle 5 - C-ITS V2I motorway focused applications
The impact data presented in this section are from the 2019 C-ITS impact assessment
support study, which reviewed and updated the information that was collected for the 2016
C-ITS deployment study. The services in Bundle 5 cover day 1 vehicle-to-infrastructure
C-ITS services, divided into two broad service types. This section covers services that are
typically more relevant to highway environments, although impacts can be realised across
the network: In-vehicle signage and speed limits, Probe Vehicle Data, Roadworks
Warning, Weather Conditions, and Shockwave Damping. As with Bundle 4 and described
in Section 5.12, safety impact overlap with the GSR is accounted for.
5.13.1. In-vehicle signage (VSGN)
Service Overview
In-vehicle signage is a vehicle-to-infrastructure (V2I) service that informs drivers of
relevant road signs in the vehicle’s vicinity, alerting drivers to signs that they may have
missed, or may not be able to see. The main purpose of this service is to provide
information, give advance warning of upcoming hazards and increase driver awareness.
Via V2I communication, information about relevant road signs is provided to the driver.
Roadside units may be mounted on traffic signs and key points along roads, informing
drivers of potentially dangerous road conditions ahead, speed limits and upcoming
junctions. Alternatively, this information may be transmitted via the local cellular network.
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This service is applicable to all vehicle and road types, although may have particular
benefits on motorways.
Impact data
Data availability for impacts directly related to in-vehicle signage was extremely limited.
The DRIVE C2X project tested six specific road signs (children, merge, pedestrian
crossing ahead, pedestrian crossing, stop, yield), however trials were on a small scale and
quantitative assessments of specific impacts were limited to two very specific road signs
(pedestrian crossing and children sign) (TNO, 2014). An overview of the general
methodology of DRIVE C2X is provided in Table 46.
A report by the US Department of Transport NHTSA also estimated the impact of several
road signs, however impacts were only given in terms of reduction in accidents and were
not further categorised by severity.
Traffic efficiency
Although in-vehicle signage may influence traffic in a very local environment the effects
are expected to be limited on an EU level, with the primary effect intended to be on safety.
As in-vehicle signage is not expected to have a significant effect this impact is not included
in the model. This is confirmed by the DRIVE C2X study, which did not consider the
effect on traffic efficiency for this service.
Fuel consumption and CO2
The primary effect of in-vehicle signage is intended to be on safety, hence the fuel
efficiency impacts are expected to be minimal. No fuel efficiency are therefore anticipated
on an EU level as a consequence of this service and it is not included as part of the model.
This is confirmed by the DRIVE C2X study, which did not consider the effect on fuel
consumption for this service.
Environmental and emissions impacts
The primary effect of in-vehicle signage is intended to be on safety, hence the emissions
impacts are expected to be minimal. No emissions benefits are therefore anticipated on an
EU level as a consequence of this service and it is not included as part of the model. This
is confirmed by the DRIVE C2X study, which did not consider the effect on emissions for
this service.
Safety
The DRIVE C2X study estimated safety impacts based on small scale trials of only two
signs: pedestrian crossing and child sign. The impact data for the high scenario is as
follows:
 Impact on fatalities: 1.04% reduction
 Impact on injuries: 0.46% reduction
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As DRIVE C2X only based the impacts on the pedestrian crossing and child road signs,
the impacts of other types of road signs were estimated based on data from the US DoT
report (John A. Volpe National Transportation Systems Center, 2008) This report
estimates that a stop sign violation warning is expected to lead to a 0.088% reduction in
annual light vehicle crashes. The same impact for a merge was assumed, stop and yield
sign, leading to the following impacts per road type:
 Motorways:
o Impact on fatalities: 1.04% reduction (from DRIVE C2X)
o Impact on injuries: 0.46% reduction (from DRIVE C2X)
 Other interurban roads:
o Impact on fatalities: 1.04% (from DRIVE C2X) + (3 x 0.088%) (applying
the value of 0.088% from US DoT report for stop sign violation and
assuming the same impact for merge, stop and yield signs) = 1.30%
reduction in fatalities
o Impact on injuries: 0.46% (from DRIVE C2X) + (3 x 0.088%) (applying
the value of 0.088% from US DoT report for stop sign violation and
assuming the same impact for merge, stop and yield signs) = 0.72%
reduction in injuries
 Urban roads:
o Impact on fatalities: 1.04% (from DRIVE C2X) + (3 x 0.088%) (applying
the value of 0.088% from US DoT report for stop sign violation and
assuming the same impact for merge, stop and yield signs) = 1.30%
reduction in fatalities
o Impact on injuries: 0.46% (from DRIVE C2X) + (3 x 0.088%) (applying
the value of 0.088% from US DoT report for stop sign violation and
assuming the same impact for merge, stop and yield signs) = 0.72%
reduction in injuries
Other impacts
No data related to other impacts was identified in the reports reviewed.
5.13.2. In-vehicle speed limits (VSPD)
Service Overview
In-vehicle speed limits are intended to prevent speeding and bring safety benefits by
informing drivers of speed limits. Speed limit information may be displayed to the driver
continuously, or targeted warnings may be displayed in the vicinity of road signs, or if the
driver exceeds or drives slower than the speed limit.
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Roadside units at key points along roads can broadcast information to drivers about speed
limits, ensuring that drivers are aware of the permitted driving speed. Alternatively this
information may be transmitted via the local cellular network. This service is applicable to
all vehicle and road types, however, may have particular benefits when warning drivers of
changing speed limits when travelling along high speed roads.
Impacts
The main data source for the impacts of in-vehicle speed limits was the DRIVE C2X
project (TNO, 2014). An overview of the general methodology is provided in Table 46.
This service was trialled at test sites in Finland, Italy, Spain and Sweden in DRIVE C2X
and the data was used to produce EU-level impact data reported in the DRIVE C2X impact
assessment.
Other studies that considered the impacts of in-vehicle speed limits include eIMPACT,
eSafetyForum Intelligent Infrastructure Work Group and SAFESPOT (TNO, VTT,
Movea, PTV, BASt, 2008), (SAFESPOT, 2010). DRIVE C2X refers to and builds on many
of these studies; the DRIVE C2X study is therefore believed to be a more reliable source
of data as it is based on more recent estimates and FOT results.
Traffic efficiency
The primary objectives of the in-vehicle speed limit service are to decrease speed and
improve safety. The increase in delay per vehicle-km found in the DRIVE C2X study
(TNO, 2014) is therefore not surprising and can be attributed to a higher awareness of
speed limits. Many traffic efficiency effects observed in the DRIVE C2X study were not
statistically significant, with the only significant results being found for motorways and
rural roads during off-peak times. The authors argue that this is because the impact was
measured at specific point on the road (which may be subject to larger variations) rather
than if speed was measured over a long stretch of road. The overall delay for different road
types is shown below:
 0.6 seconds per kilometre on motorways
o seconds per kilometre on rural roads
 No significant effect on delay on urban roads
The eIMPACT and eSafetyForum Intelligent Infrastructure Working Group studies also
considered the impact of in-vehicle speed limits on speed. The results of these studies are
summarised below:
 eSafetyForum: Speed limit information 2-10% reduction in congestion.
 eIMPACT - average change in speed:
o Motorways: 1.1% increase (low demand), 0.6% increase (high demand)
o Rural roads: 1.0% decrease (low demand), 0.9% decrease (high demand)
o Urban roads: 1.4% decrease (low demand), 1.7% decrease (high demand)
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Change in speed was only modelled for urban roads in TRT’s ASTRA model. DRIVE
C2X showed that in-vehicle speed limits did not have a statistically significant impact on
urban roads, however further trials are needed to confirm this.
As an input to the model the average speed change from the eIMPACT project was
therefore scaled for urban roads based on vehicle kilometres driven in high demand and
low demand situations, to give an average 1.40% reduction in vehicle speed in urban
areas. The reduction was only applied to passenger cars and not to public transport.
Fuel consumption and CO2
Fuel consumption benefits were seen for the in-vehicle speed limits function in the DRIVE
C2X study, which is likely to be due to a smoother driving style. Specifically, greater
awareness of speed limits may reduce sudden acceleration and braking manoeuvres. The
DRIVE C2X FOT only found a statistically significant reduction in fuel consumption on
motorways and on rural roads. The DRIVE C2X study provides impact data for two
scenarios:
 speed limit information shown only in the vicinity of road signs
 speed limit information displayed continuously
A much greater impact was observed when speed limit information was displayed
continuously (TNO, 2014). In practice, speed limit information may not be displayed
continuously if a variety of C-ITS services are implemented into a vehicle, therefore the
values for speed limit information shown only in the vicinity of road signs were used.
The impacts of in-vehicle speed limits were scaled up from FOT scale to EU-27 level based
on the number of vehicle-kilometres travelled, in order to determine absolute fuel savings
(in tonnes). The figures for the high penetration level (76%) were converted to percentages
based on the share of vehicle kilometres travelled on each road type, which gave a 2.3%
fuel saving on motorways and a 3.5% fuel saving on other interurban roads. These
values are in the range suggested by the eSafetyForum study, which stated a 2-10%
reduction in CO2 emissions (eSafetyForum, 2010).
Environmental and emissions impacts
Minor environmental benefits were seen on motorways for the in-vehicle speed limits
function in the DRIVE C2X study, which is likely to be due to a smoother driving style.
Specifically, greater awareness of speed limits may reduce sudden acceleration and
braking manoeuvres. However, on other interurban roads, DRIVE C2X estimates a small
increase in emissions, particularly PM emissions, likely due to increased braking or speed
changes when approaching new speed limits. No significant effect was observed in urban
areas.
The absolute emissions changes stated in DRIVE C2X for the high penetration level (76%)
were converted to percentage savings on each road type, based on vehicle-kilometres
driven on EU roads. The following values were inputted into the model:
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 NOx: 0.5% reduction (motorways), 0.4% reduction (other interurban roads), zero
change (urban roads)
 PM: 0.4% decrease (motorways), 4.2% increase (other interurban roads), zero
change (urban roads)
 CO: 0.2% reduction (motorways), 0.2% increase (other interurban roads), zero
change (urban roads)
 VOCs: 0.1% increase (motorways), 0.5% increase (other interurban roads), zero
change (urban roads)
Safety
The primary function of in-vehicle speed limits is intended to be reducing speeding; an
improvement in road safety is therefore expected. The DRIVE C2X study confirms this
assertion and reports significant reductions in both injuries and fatalities, however the
magnitude of these impacts varies depending on whether speed-limit information is shown
to the driver continuously or only in the vicinity of road signs. If speed limit information
is only shown in the vicinity of road signs the number of prevented fatalities is estimated
to be 121-768 in 2030, whereas if information is provided continuously, an estimated 566-
1772 prevented fatalities is expected. In practice, speed limit information may not be
displayed continuously if a variety of C-ITS services are implemented into a vehicle,
therefore the values for speed limit information shown only in the vicinity of road signs
were selected for the modelling inputs.
The values for the high scenario were converted to percentages based on projected EU
fatalities in 2030 (as stated in the DRIVE C2X report). This is equivalent to a 6.9%
reduction in fatalities and a 3.9% reduction in injuries, applied to passenger cars and
freight for all road types in the modelling.
A number of other studies covered the safety impacts of in-vehicle speed limits, as
summarised in Table 53.
Table 53: Summary of safety impacts of in-vehicle speed limits
Study Fatalities
(reduction)
Injuries (reduction) Scenario
DRIVE C2X 6.93% 3.93% High penetration (100% in
cars, overall 76% system
penetration, high safety
impact estimate)
EU-28, 2030
eIMPACT 8.7% 6.2% 100% penetration
EU-25, 2020
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SAFESPOT 7.1% 4.9% 100% penetration
EU-25, 2020
eSafetyForum 2-10% 2-10% Not stated
CODIA 7.2% 4.8% 100% penetration for
light/heavy vehicles, 55% of
driven km
The eIMPACT project estimated an 8.7% reduction in fatalities and a 6.2% reduction in
injuries, assuming 100% penetration at EU-25 level. In comparison with DRIVE C2X data,
the impact on both fatalities and injuries is higher.
SAFESPOT also assesses the impact of in-vehicle speed alerts and estimates a 7.1%
reduction in fatalities and a 4.9% reduction in injuries at an EU-25 level, assuming 100%
penetration in 2020 (SAFESPOT, 2010). The estimation of impacts is based on the
eIMPACT and CODIA studies and are comparable to those stated in DRIVE C2X.
The eSafetyForum study estimates a 2-10% reduction of fatalities/injuries. The average of
this (6%) is comparable with the DRIVE C2X figure for fatalities avoided, however it is
much higher than the figure for injuries. This may be because the impacts on fatalities and
injuries were not treated separately as part of the eSafetyForum literature review.
CODIA estimated the effect of a service called ‘dynamic speed adaptation’ at a 100%
penetration rate. The expected reduction in fatalities was stated as 7.2%, while the
reduction in injuries was estimated to be 4.8%. These figures are comparable to a number
of studies covered here.
We have used the DRIVE C2X figures as inputs to the model as the values are based on
FOT data and build on the findings of earlier EU studies in this field.
Other impacts
Stakeholder inputs during the DRIVE C2X project (TNO, 2014) suggest that user
acceptance for in-vehicle speed limits is in-line with other C-ITS services. Drivers found
warning messages useful when they exceeded the speed limit, however only 28% felt that
the system provided benefits that were not provided by other functions on the market. This
is likely due to satellite navigation systems providing this capability.
Qualitative effects of in-vehicle speed limits were a reported improvement in comfort and
safety, however the impact on stress was questionable. Mean values for these impacts were
assessed at 4.2-5.2 for comfort (on a scale from 1, strongly disagree to 7, strongly agree),
and 5.2 for safety.
There were no reported impacts on modal shift.
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5.13.3. Probe Vehicle Data (PVD)
Service Overview
The purpose of probe vehicle data is to collect and collate vehicle data, which can then be
used for a variety of applications. For example, road operators may use the data to improve
traffic management.
Also known as Floating Car Data (FCD), probe vehicle data refers to the collection of data
generated by vehicles. Information on a variety of vehicle parameters may be collected,
including positional information, time stamp and direction of motion. Driver actions such
as steering, braking, flat tyre, windscreen wiper status, air bag status, as well as weather
and road surface conditions can also be transmitted and collated. This probe vehicle data
is used to manage traffic flows, maintain roads and to alert users in hot spots, where the
danger of accidents accumulates. This service is applicable to all road and vehicle types,
although may be most useful on motorways. It has the potential to deliver safety,
efficiency, vehicle operation and environmental benefits. It can be delivered via the
presence of roadside units to aggregate and re-transmit the data, or via the use of cellular
networks.
Impacts
The main data sources for the impacts of the probe vehicle data service were the EasyWay
and eIMPACT projects. No other publically available studies that examine probe vehicle
data specifically were identified.
Traffic efficiency
In TRT’s ASTRA model, traffic efficiency impacts are only modelled on urban roads. The
majority of the benefits of probe vehicle data are expected to be realised on motorways,
therefore the impact of this service on traffic efficiency on urban roads was assumed to be
zero.
Fuel consumption and CO2
In the CODIA study, two services called speed adaptation due to accident and speed
adaptation due to poor weather were assessed. If added together, these services have
similar functionality to the probe vehicle data service described in this project. CODIA
estimated the impact on carbon dioxide emissions to be as follows (at 100% penetration in
EU-25 countries):
 Speed adaptation due to accident: 58.5 tonnes reduction
 Speed adaptation due to poor weather: 27,682 tonnes reduction
 Speed adaptation total: 27,741 tonnes reduction (EU-25)
The carbon dioxide emissions were scaled up to EU-27 level based on vehicle kilometre
data from TRT’s ASTRA and TRUST models, and then divided by the total EU carbon
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dioxide emissions stated in DRIVE C2X. This is equivalent to a 0.006% reduction in fuel
consumption in EU-27 countries.
Environmental and emissions impacts
Impacts on emissions were also given in the CODIA study for the dynamic speed
adaptation service (includes speed limit advice given as a consequence of weather,
obstacles and congestion). The results calculated in the study on an EU-25 level for a 100%
penetration scenario are summarised below:
Impact on NOx emissions:
 Speed adaptation due to accident: 0.7 tonnes reduction
 Speed adaptation due to poor weather: 490 tonnes reduction
 Speed adaptation total: 491. tonnes reduction
Impact on PM emissions:
 Speed adaptation due to accident: 0.015 tonnes reduction
 Speed adaptation due to poor weather: 5.13 tonnes reduction
 Speed adaptation total: 5.12 tonnes reduction
These values are equivalent to the following percentages at EU level:
 0.003% reduction in NOx emissions
 0.001% reduction in PM emissions
As no further data was available, the same CO reduction was assumed as for fuel
consumption (assuming a linear relationship between carbon content and emissions). For
VOC emissions, the same percentage reduction as for fuel consumption (0.006%) was
applied.
Safety
The safety impacts of probe vehicle data are primarily related to extended probe vehicle
data, where the emphasis is on informing the driver about adverse road conditions ahead,
for example adverse weather conditions. Safety impacts of probe vehicle data were
reported in the EasyWay study (EasyWay, 2012). The following impacts were estimated
(for EU-27, 100% penetration):
 Injury accidents and injuries: overall 2.8% reduction (4.9% on motorways, 4.1%
on interurban and rural roads, and 2.0% on urban roads)
 Fatal accidents and fatalities: overall 2.4% reduction (3.3% on motorways, 2.8%
on interurban and rural roads, and 1.6% on urban roads)
Other impacts
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No data related to other impacts was identified in the reports reviewed.
5.13.4. Roadworks warning (RWW)
Service Overview
Roadworks warnings enable road operators to communicate information about road works
and restrictions to drivers. This allows drivers to be better prepared for upcoming
roadworks and potential obstacles in the road, therefore reducing the probability of
collisions.
Roadside units are mounted on road works, enabling messages and instructions to be sent
to approaching drivers, either directly via short-range communications, or via the cellular
network. This service is applicable to all road and vehicle types.
Impacts
The main data source for the impacts of roadworks warning was the DRIVE C2X project
(TNO, 2014) An overview of the general methodology is provided in Table 46. For
roadworks warning, tests were carried out at test sites in Finland, Italy and Sweden. In
DRIVE C2X, this service is evaluated in the same section as ‘obstacle warning’ and ‘car
breakdown warning’, as the services perform a similar function, act via similar
mechanisms and present information to drivers in a similar manner.
Another data source considered was the NordicWay project (Innamaa et al., 2017) which
considered the safety impacts of roadworks warning, delivered by roadside systems.
NordicWay deployed cooperative services via a cellular network along a corridor spanning
Finland, Sweden, Denmark and Finland. ‘NordicWay Coop’ was a project along the
Finnish part of the corridor that deployed safety related services. Data from this project
has been examined for the roadworks warning service impacts.
No other publicly available studies that examine roadworks warning specifically were
identified.
Traffic efficiency
The traffic efficiency impacts of the roadworks warning service are expected to be minimal
as its purpose is to improve safety, rather than prevent traffic jams (TNO, 2014). No traffic
efficiency impacts are expected when scaled up to EU level and it is not included as part
of the model. This is confirmed by the DRIVE C2X study, which did not consider the
effect on traffic efficiency for this service.
Fuel consumption and CO2
Fuel efficiency impacts are expected to be negligible for this service when scaled up to an
EU level. This is confirmed by the DRIVE C2X study, which did not consider the effect
on fuel consumption for this service.
Environmental and emissions impacts
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Impacts on vehicle emissions impacts are expected to be negligible for this service when
scaled up to an EU level. This is confirmed by the DRIVE C2X study, which did not
consider emissions impacts for this service.
Safety
The key objective of the roadworks warning service is to improve safety, which as
described in the DRIVE C2X study can be achieved by reducing the likelihood of several
different types of collisions. The types of collisions expected to be prevented the most by
this service are side-by-side collisions, single vehicle collisions with obstacles and rear
collisions (TNO, 2014). Specifically, the service is expected to:
 Warn drivers about upcoming roadworks (especially those outside of the field of
vision) and therefore limit unsafe manoeuvres.
 Increase driver alertness.
 Help to avoid sudden braking or steering/swerving manoeuvres.
 Reduce speed in the proximity of roadworks, thus decreasing the severity of
potential injuries.
DRIVE C2X scaled up safety impacts based on Swedish road safety statistics (TNO, 2014),
which estimate that 2.3% of injuries and 3% of fatalities occur due to roadworks. The study
assumes 100% infrastructure and vehicle penetration and assumes the following:
 Roadworks warning would only be effective for accidents caused due to inattention
or lack of awareness (80-90% of accidents).
 Includes winter road maintenance work which does not take place in all parts of
EU28. In those countries, the number of road works may be higher overall and may
be made all year round (in Nordic countries, road works only take place in the
summer).
 Effectiveness of the system was estimated to be 80-90% for rear collisions, single
vehicle collisions with pedestrians and other obstacles. This high level of
effectiveness is due to drivers expecting these types of hazards and has been based
on previous naturalistic driving studies (Dingus, 2008).
 80-90% system effectiveness was also assumed for ‘other single vehicle accidents’.
This category primarily includes driving off road during a panic manoeuvre, which
would most likely be significantly reduced if roadworks warnings were
operational.
 The effectiveness was estimated to be 70–80% for frontal collisions. This also
represents panic manoeuvres.
 60-70% effectiveness for other accident types. This lower effectiveness is due to
the unexpected nature of these types of accident.
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NordicWay also considered accidents at roadwork sites and in their influence area, which
was assessed to be 1.5-2.2% of total road injury accidents. This value is taken from
estimates of Danish roadwork related injury accidents. The following assumptions are also
made:
 The main causal factor for roadworks related accidents is inattention around the
critical moment/ location (Innamaa et al., 2017) and it is this factor that the warning
system is attempting to influence.
 In general, the impact of roadworks warning was assumed to be less than for
warnings of more surprising incidents such as accidents and obstacles on the road.
 The coverage of roadworks by the warning system is assumed to be 95-100%.
 A target year of 2030 is included in the analysis, which assumed penetration across
the whole main road network in Finland (31-65% of total network).
In the DRIVE C2X high scenario, the overall safety impact for this service was calculated
to be 209 prevented fatalities and 9,939 prevented injuries in EU-28 countries if the service
was deployed in 100% of passenger cars (equivalent to a 76% fleet penetration). This is
equivalent to a 1.9% decrease in fatalities and a 1.5% decrease in injuries.
The Drive C2X values were reduced by 30%, taking into consideration the lower safety
impacts reported by NordicWay Coop. An average of the two project’s values is not taken
as the NordicWay values represent only a 31-65% penetration rate across Finland’s road
network. Furthermore, impacts on fatal accidents were assessed based on estimates of
injury related accidents occurring at roadworks, which is lower than Swedish road safety
statistics estimate for fatal accidents.
A 1.3% decrease in fatalities and a 1.1% decrease in injuries were used as inputs to the
model. Impacts were assumed to be the same on all road types.
Other impacts
Subjective assessment carried out during the DRIVE C2X study using stakeholder input
suggested that roadworks warning has limited usefulness, however the willingness to use
the service remained rather high at 79%. Further assessment suggested that the impacts of
the service on stress, comfort and feelings of uncertainty were minimal. There were no
reported impacts on modal shift, or a change in travel patterns in the DRIVE C2X study.
5.13.5. Weather conditions (WTC)
Service Overview
The objective of this service is to increase safety through providing accurate and up-to-
date local weather information. Drivers are informed about dangerous weather conditions
ahead, especially where the danger is difficult to perceive visually, such as black ice or
strong gusts of wind.
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Vehicles are sent information from roadside units warning the driver of dangerous, or
changeable weather conditions. Alternatively, the messages may be transmitted via the
cellular network. This service is applicable to all roads and vehicle types.
Impacts
The main data source for the impacts of the weather conditions service was the DRIVE
C2X project (TNO, 2014). An overview of the general methodology is provided in Table
46. FOTs took place in Finland and Spain as part of this project, with a total of 39
participants. In Finland, slippery road warnings were presented in winter conditions, while
in Spain warnings about rainy conditions were shown.
Other studies that considered the impacts include eIMPACT (TNO, VTT, Movea, PTV,
BASt, 2008), CODIA (VTT, TRL, 2008), eSafetyForum (eSafetyForum, 2010), EasyWay
(EasyWay, 2012), SAFESPOT (SAFESPOT, 2010) and NordicWay (Innamaa et al.,
2017). Much of the safety impacts data in these projects build on and the eIMPACT study.
As the DRIVE C2X project incorporates FOT results into their estimates, values from this
data source were used.
Traffic efficiency
The primary effect of the weather conditions warning is intended to be on safety, hence
the traffic efficiency impacts are expected to be minimal.
The DRIVE C2X study did not assess the effect of this service on traffic efficiency, citing
a lack of results to be able to qualitatively evaluate the service. CODIA assessed a “local
danger warning due to poor weather” service, which led to an increase of 28,489 thousand
hours on the road per year in EU25 at a 100% penetration rate. When converted to a
percentage, the effect on time spent on the road is less than 0.1%, applied to both cars
and public transport on all road types in the modelling.
Another service, ‘speed adaptation due to poor weather’ was also separately assessed in
CODIA. The impacts associated with this service have not been included in this IA as the
service definition for weather warning does not state that speed limit information will be
provided to the driver.
Fuel consumption and CO2
The primary effect of the weather conditions warning is intended to be on safety, hence
the fuel consumption impacts are expected to be minimal on an EU level. The DRIVE C2X
study did not assess the effect of this service on fuel consumption, however CODIA
assessed a service called ‘local danger warning due to poor weather’. At a 100%
penetration level, a 47,407 tonnes per year reduction in carbon emissions at EU-25 level
was calculated (VTT, TRL, 2008). This was scaled to EU-27 level based on vehicle
kilometre data from TRT’s TRUST and ASTRA models. The resulting value (48,444) was
divided by the total annual EU CO2 emissions stated in DRIVE C2X. This gives a 0.005%
reduction in fuel consumption at an EU-27 level, which was applied to both cars and
public transport on all road types in the modelling.
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Environmental and emissions impacts
Minor emissions benefits for the ‘local danger warning due to poor weather’ service were
reported in CODIA. At a 100% penetration level, the following impacts on emissions were
calculated by CODIA (VTT, TRL, 2008):
 752.50 tonnes per year reduction in NOx emissions at EU25 level
 9.15 tonnes per year reduction in particulate matter emissions at EU25 level
These values are equivalent to the following percentages at EU level:
 0.02% reduction in NOx emissions
 0.01% reduction in PM emissions
As further data was not available, the same CO reduction as for fuel consumption was
assumed (assuming a linear relationship between carbon content and emissions). For VOC
emissions, the same percentage reduction as for fuel consumption was applied. These
values were applied to cars and freight vehicles on all road types in the modelling.
Safety
The objective of this service is to increase safety in adverse weather conditions such as ice,
fog, rain, snow, sleet, hail and wind. The main impacts are expected to occur via direct in-
vehicle modification of the driving task after drivers receive information about adverse
weather conditions. Specifically, this service is expected to have a number of impacts:
 In conditions where the danger can easily be perceived (such as heavy rain), the
notification serves as a reminder of the potential danger ahead, and increasing
driver awareness.
 In situations where the danger cannot be easily be perceived (such as strong cross-
winds, or black ice) drivers will receive valuable information regarding local
weather conditions/hazards that they otherwise would not have known about.
 In both of the above situations, the driver will be more prepared for the hazard and
will have the opportunity to adjust their speed accordingly, preventing sudden
braking, accelerating, swerving or overtaking manoeuvres.
It is thought that any rebound effects from over-reliance on the system will be negligible.
This is because the information used to deliver the service will come partially from other
vehicles further ahead and therefore drivers cannot assume that there will always be
suitably-equipped vehicles ahead (TNO, 2014).
DRIVE C2X scaled up safety impacts based on the impact on driver speeds, driver
awareness and the headway between vehicles, using values from FOT data, expert
estimates and estimates from the CODIA and eIMPACT projects. For the high scenario in
2030, this resulted in a projected 3.43% reduction in fatalities and a 3.35% reduction in
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injuries, applied to cars and freight on all road types in the modelling. These values
are supported by those reported in the NordicWay project.
Potential safety impacts of the weather conditions service are covered in many other
studies, as summarised in Table 54. The values from DRIVE C2X are used as an input to
the modelling in this project as they are based on FOT data and build on previous EU
studies. A discussion of results from other studies is provided below for comparison.
Table 54: Summary of safety impacts of weather conditions services from EU studies
Study Fatalities
(reduction)
Injuries
(reduction)
Scenario
DRIVE C2X 3.43% 3.35% 76% penetration, high safety
impact estimate
EU-28, 2030
NordicWay 3.5% 3.9% 100% penetration Finland,
2030
EasyWay 16.5% (average) 8.5% (average) 100% penetration
EU-27, 2030
eIMPACT 4.5% 2.8% 100% penetration
EU-25, 2020
SAFESPOT 1.6% (V2I)
16.4% (V2V)
0.7% (V2I)
8.6% (V2V)
100% penetration
EU-25, 2020
eSafetyForum 2-4% 2-4% Not stated
Estimations in the EasyWay project are based on the methodology from the CODIA project
and state that if the base speed is 80km/h, there will be a 5% decrease in injury crash risk
in adverse conditions, if low friction warnings are displayed, while a 12% decrease in
injury collisions is expected for a fog warning. For a fatal crash risk, the percentage
reductions are 10% for low friction warning and 23% for fog warnings. EasyWay averaged
these figures to give overall impacts of 8.5% on injury crashes and 16.5% on fatal crashes.
eIMPACT evaluated a service called wireless location danger warning, one aspect of
which is weather warning. A 4.5% reduction in fatalities and a 2.8% reduction in injuries
was estimated, assuming 100% penetration on an EU-25 level. These values are slightly
higher than those estimated by DRIVE C2X, however this is likely to be because
eIMPACT also considered stationary vehicle warning to be part of this service.
SAFESPOT assesses the impact of two weather warning services: road departure (V2V)
and hazard and incident warning (V2I). The road departure (V2V) use case informs the
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drivers of road conditions, such as a slippery road. SAFESPOT estimates an 8.6%
reduction in injuries and a 16.4% reduction in fatalities, which is based on values obtained
from the eIMPACT and CODIA projects. These figures are almost identical to EasyWay.
The hazard and incident warning (V2I) use case includes weather conditions that result in
reduced friction on the road or reduced visibility, such as ice, rain or fog and was shown
to be significantly less effective than the V2V service. The estimation of impacts are again
based on the eIMPACT and CODIA studies. SAFESPOT estimates a 1.6% reduction in
fatalities and a 0.7% reduction in injuries at an EU-25 level, assuming 100% penetration
in 2020 (SAFESPOT, 2010). These values are slightly lower than other reports reviewed
in this section.
Finally, eSafetyForum reported that a weather conditions service could lead to a 2-4%
reduction of fatalities/injuries. This is consistent with the DRIVE C2X figures.
Other impacts
A survey of drivers in the DRIVE C2X study indicated that 76% of drivers agreed that the
weather conditions warning was useful, which is lower than the average for all services
tested. This is likely due to the fact that drivers were more enthusiastic about particular
types of weather warnings than others. For example, qualitative feedback provided by test
drivers showed they were particularly receptive to warnings about potentially more serious
hazards such as ice on the road, however they were less enthusiastic about receiving
repetitive rainy conditions warnings while driving along a straight road. User acceptance
is therefore likely to be dependent on the type of weather warning and how drivers value
each type of weather warnings.
Further assessment showed that test drivers felt an increased sense of safety and comfort
as a result of this service. On a scale of 1 (strongly disagree) to 7 (strongly agree), the mean
value for increased feeling of comfort was 4.8 and for safety was 5.5.
There were no reported impacts on modal shift, or a change in travel patterns in the DRIVE
C2X study.
5.13.6. Shockwave damping (SWD)
Service Overview
Shock wave damping aims to smooth the flow of traffic, by damping traffic shock waves.
Real-time traffic data is used to feed advisory speeds to cars to smooth out speed variations.
This service is applicable to all vehicle types and is particularly relevant to motorways.
Again, it could be delivered via roadside units, or the cellular network.
Impacts
The main data source for the impacts of shockwave damping was the CODIA project
(VTT, TRL, 2008). No other publically available studies that specifically examine this
service were identified. The majority of the benefits of shockwave damping are expected
to be on motorways, therefore the impact of this service on urban roads and other
interurban roads is assumed to be zero.
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Traffic efficiency
CODIA assessed a dynamic speed adaptation due to congestion service that closely
matches the shockwave damping service. As a consequence of this service, the authors
estimated an increase of time spent on the road of 63.5 thousand vehicle hours per year in
EU25 at 100% penetration rate. In TRT’s ASTRA model, traffic efficiency impacts are
only modelled on urban roads. This service is not expected to have an impact on urban
roads, therefore the impact on traffic efficiency was assumed to be zero.
Fuel consumption and CO2
The dynamic speed adaptation due to congestion service assessed in CODIA estimates a
reduction of 26,232 tonnes per year of carbon emissions at EU-25 level in a 100%
penetration scenario (VTT, TRL, 2008). When calculated as a percentage, these effects are
extremely small (0.005% reduction). It is assumed that all fuel consumption benefits will
occur on motorways and that there will be zero impact on fuel consumption on other
interurban roads, and urban roads.
Environmental and emissions impacts
The dynamic speed adaptation due to congestion service assessed in CODIA calculated
the following impacts on vehicle emissions if the service is deployed at a 100% penetration
level in EU-25 countries (VTT, TRL, 2008):
 363 tonnes per year reduction in NOx emissions at EU25 level
o tonnes per year reduction in particulate matter emissions at EU25 level
When calculated as a percentage, these effects are extremely small (less than 0.1%).
Safety
One of the primary objectives of this service is to improve safety on high-speed roads. In
CODIA, estimates of safety impacts were presented for the dynamic speed adaptation due
to congestion/obstacles at a 100% penetration level (VTT, TRL, 2008). The study
estimates a 13% reduction in fatalities and a 10.3% reduction in injuries on motorways.
The inclusion of obstacle warnings in the CODIA definition results in additional
functionality to the shockwave damping service defined in this IA, therefore the safety
impacts of the hazardous location service were subtracted from the figures reported in
CODIA. This gave the following values, which were used in the modelling:
 Reduction in fatalities on motorways: 7.8%
 Reduction in injuries on motorways: 5.0%
Other impacts
No data related to other impacts was identified in the reports reviewed.
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5.14. Bundle 5 - C-ITS V2I urban only applications
The impact data presented in this section are from the 2019 C-ITS impact assessment
support study, which reviewed and updated the information that was collected for the 2016
C-ITS deployment study. In this second group of Bundle 5 V2I services, the services are
more focused on intersection environments and include: Green Light Optimal Speed
Advisory, Signal violation/Intersection safety, and Traffic signal priority request by
designated vehicles. As with Bundle 4 and described in Section 5.12, safety impact overlap
with the GSR is accounted for.
5.14.1. Green Light Optimal Speed Advisory (GLOSA) / Time to Green (TTG)
Service Overview
GLOSA provides speed advice to drivers approaching traffic lights, reducing the
likelihood that they will have to stop at a red light, and reducing the number of sudden
acceleration or braking incidents. This is intended to provide traffic efficiency, vehicle
operation (fuel saving) and environmental benefits by reducing unnecessary acceleration.
Traffic lights are connected to a roadside unit, which broadcasts information to nearby
vehicles informing them of the traffic light phase schedule. This will enable vehicles to
calculate optimal speed of approach. Time to green information may also be presented to
drivers. It is applicable to all vehicle types and is particularly suitable in urban areas, where
intersections are generally sited. Whilst it is expected to rely primarily on V2I direct short-
range communication, a number of projects are looking to demonstrate its effectiveness
using high-speed (e.g. 4G/5G) cellular networks.
Impacts
The main data source for the impacts of GLOSA was the DRIVE C2X project (TNO,
2014). An overview of the general methodology is provided in Table 46. For GLOSA, tests
were carried out at test sites in Germany, Spain and Sweden. However, the number of
events available after filtering in Sweden was too low to provide a good comparison of
with and without-service behaviour. Similarly, the data from the Spanish test site was
interpreted as a first order effect rather than an effect of GLOSA. Hence, pooling the
GLOSA data was not straightforward due to the large differences in experimental set-up.
Other studies that considered the impacts include the Dutch ODYSA project and
subsequent follow-ons; Beek et al. 2013 and van Katwijk et al. These studies were taken
into account in the DRIVE C2X results and hence were not considered further here.
Traffic efficiency
In DRIVE C2X, traffic efficiency was assessed by naturalistic driving tests on urban roads
and by simulations. The results were dependent on the level of traffic, with tests showing
a slight overall increase in delay per traffic light, which was attributed to the slower speed
of approach. The time spent stationary at traffic lights may be reduced by this service but
the effects are not statistically significant. Results from the test site in Germany indicated
that driver behaviour may become smoother and results from the literature surveyed by the
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authors of DRIVE C2X are inconclusive. The DRIVE C2X study team fed FOT data into
a model, in order to calculate impacts. They reported an unexpected result of a 9% increase
in delay for the implementation of GLOSA, however this was probably due to the way the
yellow light was simulated in the model.
Overall, the effects on traffic efficiency are assumed to be small because (1) the system is
not necessary when the driver arrives at a light that is already green; and (2) GLOSA has
limited potential to affect the possibility of a driver arriving at a red light.
As the results currently stated in the literature are inconclusive, it is assumed that this
service will not have an impact on traffic efficiency in urban areas.
Fuel consumption and CO2
The primary effect of GLOSA is expected to be on fuel efficiency and environmental
impacts due to reduced braking and acceleration while passing through traffic lights. The
DRIVE C2X study shows that impacts are dependent on vehicle technology, with hybrids
showing lower potential for improvement. The impact on motorways is assumed to be
negligible, since GLOSA is only effective at traffic light controlled intersections. The
study reported the following specific effects on urban roads, in the high penetration
scenario:
 A reduction in fuel consumption of 3% when approaching an intersection. The
authors scaled this impact to EU-27 level based on the number of approaching
vehicles at signalised intersections in EU-27 countries. The number of approaching
vehicles per year at signalised intersections in the EU-27 was estimated to be 1.708
trillion, concentrated on rural and urban roads (estimated to be 70% for urban and
30% for rural), as shown in Table 55. Although the amount of signalised
intersections was known at the EU level, the number of approaching vehicles was
estimated based on data from the Netherlands, as information for the EU was not
available.
Table 55: Estimation of the number of vehicles approaching intersections in EU-27 countries per year
(Source: DRIVE C2X)
Road type Low demand (billions) High demand (billions)
High speed roads 0 0
Rural roads 358.7 153.7
Urban roads 837.0 358.7
 An overall reduction in fuel consumption of 219,729 tonnes on rural roads and
512,702 on urban roads when scaled up to EU-27 level.
 This is equivalent to a 0.1% reduction in fuel consumption on rural roads and
a 0.7% reduction in fuel consumption on urban roads.
The DRIVE C2X values are lower than an earlier TNO study which estimated that traffic
signal optimisation could lead to a 2% reduction in CO2 emissions on an EU-27 level. The
DRIVE C2X figures were used in the modelling as they are based on FOT data.
Environmental and emissions impacts
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Only the DRIVE C2X study presented detailed results about the impact of GLOSA on
vehicle emissions. Per intersection approach, the following effects were observed:
 Reductions in CO and HC emissions of 15.5% and 40.2%. The levels of changes
to these pollutants are large because they are highly sensitive to acceleration and
braking.
 Reduction in NOx emissions of 3.2%
The authors scaled these figures up to EU-27 level by road type to give the impact on each
pollutant in tonnes per year. These absolute emissions reductions were converted to
percentages based on the annual pollutant emissions by road type from TRT’s ASTRA and
TRUST models. The following inputs were used in the model:
 CO: 0.3% reduction (other interurban roads), 0.8% (urban roads)
 NOx: 0.1% reduction (other interurban roads), 0.2% (urban roads)
 VOCs: 0.5% reduction (other interurban roads), 0.6% (urban roads)
 PM: 0.1% reduction (other interurban roads) , 0.0% (urban roads)
Safety
GLOSA was found to have minor safety benefits in the DRIVE C2X study (TNO, 2014),
mainly as a consequence of the lower number of vehicles needing to stop at traffic lights.
Since the primary objective of GLOSA is not safety-related, it is to be expected that the
overall impacts are small.
Specifically, positive effects that were expected are:
 On average, drivers will need to stop at traffic lights less with GLOSA. The
probability of a rear-end collision is therefore reduced.
 Smoother driving behaviour is expected on the approach to traffic lights, reducing
both the risk and severity of a collision.
 Drivers will, on average, approach traffic lights at a lower speed with GLOSA.
 Abrupt and indecisive braking behaviour will be eliminated due to the information
GLOSA provides to drivers. This will reduce the risk and impact of rear-end
crashes, limit red light violations and reduce angle-crashes.
However, the study also suggests that GLOSA may be less effective and less reliable for
adaptive or actuated traffic lights, as these are dependent on unpredictable traffic flows.
The service may also distract drivers, resulting in decreased attention on the road ahead,
due to focussing on the in-vehicle advisory system. This is expected to be minor and may
be limited further by good design on the in-vehicle interface.
The effectiveness of GLOSA was found to be highly dependent on penetration rate and
traffic intensity. Safety effects were presented as a percentage reduction in fatalities or
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injuries in 2030 for 100% infrastructure penetration. In the high scenario in 2030, the
average fatalities prevented was estimated to be 0.1% on both urban and rural roads,
while the average number of injuries prevented was estimated to be 0.1% on rural roads
and 0.3% on urban roads.
Other impacts
Stakeholder inputs during the DRIVE C2X project suggest that user acceptance for
GLOSA is very high, with 86% of drivers rating the service as useful, while 50% claimed
they would be willing to pay for use of the feature if it was available in their vehicle (VTT,
TRL, 2008).
Qualitative effects of GLOSA were reported as improvements in terms of decreased stress
and uncertainty, and an increased feeling of safety and comfort. The typical mean
agreement values for comfort were 4.9-5.6 (on a scale from 1, strongly disagree to 7,
strongly agree), for safety approximately 4.8 and for stress 4.7-5.2. Stress and uncertainty
were also assessed on a scale from -3 to 3 (decrease-increase), and the typical mean values
for those scales were approximately -0.5 for stress and from -1.0 to -0.2 for uncertainty.
There were no reported impacts on modal shift.
5.14.2. Signal violation/Intersection safety (SigV)
Service Overview
The primary objective of this service is to reduce the number and severity of collisions at
signalised intersections.
This service, also known as the Red Light Violation Warning (RLVW), allows for drivers
to be warned when they are in danger of violating a red light, or when it is probable that
another vehicle is going to make a red light violation. It is applicable to all vehicle types
and is particularly suitable in urban areas, where intersections are generally sited.
Impacts
The main data sources for the impacts of signal violation/intersection safety were the
eIMPACT project (TNO, VTT, Movea, PTV, BASt, 2008) and SAFESPOT study. An
overview of the general methodology for the eIMPACT study is provided in Table 47.
Traffic efficiency
The SAFESPOT study assumes that no traffic impacts are experienced but refers to the
statement in the eIMPACT study that traffic effects are expected but have not been proven
(SAFESPOT, 2010). As no quantitative estimates have been given in the literature, it is
assumed that this service will not have an impact on traffic efficiency.
Fuel consumption and CO2
No data was identified for this impact category in the reports reviewed. Fuel consumption
impacts for this service are assumed to be zero.
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Environmental and emissions impacts
No data was identified for this impact category in the reports reviewed. Impacts on vehicle
emissions for this service are assumed to be zero.
Safety
The primary objective of this service is to improve safety at traffic intersections. A review
of the reports covering this service revealed that the intersection safety service is defined
differently depending on the study, with some studies including additional functionality
such as GLOSA. A summary of the safety impacts stated in the studies reviewed is given
in Table 56.
Table 56: Summary of safety impacts of the intersection safety service reported in other European studies
Study Fatalities (reduction) Injuries (reduction) Scenario
eIMPACT 3.9% (includes
GLOSA / TTG)
7.3% (includes
GLOSA / TTG)
100% penetration
EU-25, 2020
SAFESPOT 0.7% (V2V left-turn
assist only)
3.1% (V2I red light
violation, left and
right turn assistance)
2.2% (V2V left-turn
assist only)
4.8% (V2I red light
violation, left and right
turn assistance)
100% penetration
EU-25, 2020
CODIA 3.7% 6.9% 100% penetration,
assuming all vehicles
were equipped, regardless
of the year.
The eIMPACT study states 3.9% reduction in fatalities, 7.3% reduction in injuries,
assuming 100% penetration in at EU-25 level in 2020. GLOSA/TTG functionality is also
included in the eIMPACT definition of this service. If the safety impacts of GLOSA (the
high scenario in the DRIVE C2X study estimates a 0.1% reduction in fatalities and a 0.3%
reduction injuries) are subtracted from the impact predicted by eIMPACT, the impact
would be a 3.8% reduction in fatalities and a 7.0% reduction in injuries. These are very
similar to those suggested by CODIA (VTT, TRL, 2008).
The SAFESPOT study evaluated two intersection safety functions. The first function, a
V2V service called “lateral collision – road intersection safety” assessed the impact of in-
vehicle left-turn assistance (SAFESPOT, 2010). Assuming 100% penetration in the EU-
25 in 2020, the estimated impact of this service is a 0.7% reduction in fatalities and a 2.2%
reduction in injuries. These results are based on the PReVAL project, which follows the
same methodological approach implemented by the eIMPACT study. Another intersection
safety function evaluated by SAFESPOT was the “Intelligent Cooperative Intersection
Safety system – IRIS” service, which is based on V2I communication. This service
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primarily aims to prevent red light violations, although also includes left and right turn
assistance. The estimated impact of this service, assuming 100% penetration, is a 3.1%
reduction in fatalities and a 4.8% reduction in injuries at EU-25 level (SAFESPOT, 2010).
These results are based on the findings of the eIMPACT and CODIA projects. If the
impacts of the two SAFESPOT intersection safety services are added together, a 3.8%
reduction in fatalities and a 7.0% reduction in injuries is found.
The CODIA study also assessed the impact of cooperative intersection collision warning.
This report estimated a 3.7% reduction in fatalities and a 6.9% reduction in injuries at a
100% penetration rate, providing the system is used in all intersections in the EU (VTT,
TRL, 2008).
Based on the above, the most appropriate figure was selected as the eIMPACT estimation
(with GLOSA impacts subtracted). A 3.8% reduction in fatalities and a 7.0% reduction
in injuries on urban roads, and other interurban roads were used as inputs to the
modelling. These percentages were applied to all vehicle types and are very similar to
those stated by the SAFESPOT and CODIA studies.
Other impacts
No data related to other impacts was identified in the reports reviewed.
5.14.3. Traffic signal priority request by designated vehicles (TSP)
Service Overview
The traffic signal priority request by designated vehicles allows drivers of priority vehicles
(for example emergency vehicles, public transport, HGVs) to be given priority at
signalised junctions.
This service works by either extending or terminating the current traffic light phase, to
ensure that the required phase is displayed. Different levels of priority can be applied,
depending on the vehicle type. For example, emergency vehicles may be given the highest
priority, whereas the appropriate level of green priority for a public transport vehicle may
be dependent on its current status, i.e. whether it is on-time or behind schedule. This has
the potential to deliver a variety of benefits. Safety benefits may be gained by extending
the phase for emergency vehicles travelling at speed, efficiency benefits for public
transport and environmental benefits gained when reducing the need for vehicles to
repeatedly brake and accelerate through signalised intersections. This service is most
suitable for urban environments and is applicable for all vehicle types except passenger
cars. Whilst it is expected to rely primarily on V2I ITS-G5 communication, a number of
projects are looking to demonstrate its effectiveness using high-speed (e.g. 4G/5G) cellular
networks.
Impacts
The main data sources for the impacts of the traffic signal priority request by designated
vehicles service were the eSafetyForum Intelligent Infrastructure Working Group’s Final
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Report and the COMeSafety project. An overview of the general methodology of the
eSafetyForum report is provided in Table 51.
Despite several European FOTs trialling this service, no other publically available studies
that specifically examine traffic signal priority request by designated vehicles as a C-ITS
service were identified.
The limited information from the above two reports was therefore supplemented by
additional desk research into traffic signal priority systems – this yielded one particularly
useful source of information, namely a study by the UITP Working Group (TfL, TRL,
University of Southampton, 2009) on the interaction of buses and signals at road crossings.
This study analysed a number of European city bus priority projects, summarising travel
time reduction data for buses equipped with a variety of bus priority systems allowing them
to interact with traffic lights to smooth their passage through signalised intersections. One
such example is the SCOOT system currently being trialled by Transport for London.
Whilst not using the ITS-G5 protocols discussed in this study, some of the systems
discussed in this study could loosely fall within the definition of C-ITS services and
operate through very similar mechanisms to the C-ITS service discussed here. It was
therefore deemed appropriate to use input data from this study to estimate impacts data
from first principles.
Traffic efficiency
Traffic signal priority request will only be available to certain vehicles on other interurban
roads and urban roads. For the purposes of the modelling, it is assumed that this service
will only apply to public transport and not passenger cars or freight vehicles. In most
situations, there will also be secondary effects on non-bus users. This is captured in the
modal shift element of TRT’s ASTRA model.
The eSafetyForum literature review suggests that requesting green/signal priorities can
lead to a 1-2% reduction in congestion, however this cannot be easily translated into an
impact on urban travel speed, which is the required input for the modelling.
In the absence of data from specific C-ITS studies, data from the UITP Working Group
report was therefore used as an input to the model. Quantitative estimates of travel time
savings for bus priority systems were given for trials in the following cities: Aalborg,
Cardiff, Genoa, Gothenburg, Helsinki, Prague, Stockholm, Stuttgart, Toulouse and Turin.
The average saving was a 9.2% reduction in travel time for buses equipped with some
form of traffic signal priority system.
Fuel consumption and CO2
Reduced fuel consumption is one of the main objectives of this service. The eSafetyForum
report suggests that requesting green/signal priorities can lead to a 1-3% impact reduction
in carbon dioxide emissions, while results of the FREILOT project show that HGVs
equipped with this service reported reductions in fuel consumption of up to 20% (ERTICO,
2012). The FREILOT project was a FOT based on 11 intersections, with 7 trucks equipped
with a number of services, including traffic signal priority, energy efficient driving (which
provided speed advice and indicated when to shift up or down in order to save energy) and
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remote parking spot booking for loading and unloading. However given the lack of
references in the eSafetyForum output and the difficulty in separating traffic signal priority
from other services in the FREILOT project, it was decided to estimate fuel consumption
and CO2 savings using the results of the UITP Working Group study referenced above.
To this end, the average speed of buses without any traffic signal priority service installed
was estimated from the UITP Working Group study at 15.3 kph, alongside the improved
speed (9.2% reduction in time spent travelling) of 17.2 kph. This difference in speed was
used as an input to Ricardo Energy and Environment’s speed-emissions curve model,
which is able to estimate the impact on CO2/fuel consumption, NOx and PM10 emissions.
The total improvement in fuel consumption and CO2 emissions was therefore estimated as
8.28% across all buses in urban environments.
Environmental and emissions impacts
NOx and PM emissions were estimated using the same speed-emissions curve model as for
fuel consumption/CO2. Total improvement in NOx and PM emissions were estimated at
8.04% and 8.17% respectively across all buses in urban environments.
For CO and VOC emissions, these were assumed to be proportional to fuel consumption
savings, and therefore estimated at an 8.28% reduction for urban buses.
Safety
No data was identified for this impact category in the reports reviewed and given that this
service will most likely only be available to a limited number of vehicles, it is assumed
that the impact on safety at an EU-level will be negligible for this service and it is not
included in the model.
Other impacts
No data related to other impacts was identified in the reports reviewed.
5.15. Bundle 6 - Vulnerable road user protection – pedestrians and cyclists
(VRU)
Service Overview
This is a safety focussed service, which is intended to protect vulnerable road users. In this
vase vulnerable road users are considered to be pedestrians and cyclists only.
This service is designed to increase safety by alerting drivers of the presence of vulnerable
road users (those outside the vehicle such as pedestrians, cyclists). This may be achieved
via communication with a smartphone, or in the case of cyclists, via communication with
a C-ITS device fitted on the bike. In the case that installing direct short-range capability is
not practical within smartphones, this service could be based on a cellular technology,
provided it offers sufficiently low latency. Vulnerable road user protection is applicable to
all vehicle types and is expected to bring safety benefits to all road types, however the
majority of benefits are expected to be on urban roads.
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Impacts
The eIMPACT project evaluated a non-cooperative intelligent transport service called
“pre-crash protection of vulnerable road users”. This is similar to the vulnerable road user
protection service evaluated in this IA, however in eIMPACT it was not considered to be
a cooperative system and was assumed to operate by detecting vulnerable road users via
sensors. The two services are likely to present information to the driver in a similar manner
and safety impacts will occur via similar mechanisms, therefore the data presented can be
applied to the cooperative service.
Traffic efficiency
No data was identified for this impact category in the reports reviewed. It is assumed that
this service will not have an impact on traffic efficiency at an EU level.
Fuel consumption and CO2
No data was identified for this impact category in the reports reviewed. It is assumed that
this service will not have an impact on fuel consumption at an EU level.
Environmental and emissions impacts
No data was identified for this impact category in the reports reviewed. It is assumed that
this service will not have an impact on vehicle emissions at an EU level.
Safety
Due to the absence of other data, data from the eIMPACT project for the “pre-crash
protection of vulnerable road users” was referenced. This was not considered to be a
cooperative system, however the results provide a good indication of the expected impacts
of a similar cooperative service, as both services are expected to display similar
information to the driver.
Assuming a 100% penetration in EU-25 countries, the eIMPACT study estimated a 1.8%
reduction in fatalities and a 1.9% reduction in injuries for the pre-crash protection of
vulnerable road users (TNO, VTT, Movea, PTV, BASt, 2008). Discussions with experts
confirmed that the majority of benefits of this service will be seen in urban areas. A 1.8%
reduction in fatalities and a 1.9% reduction in injuries has therefore been used for
other interurban roads, and urban roads, applied to all vehicle types. This service was
assumed to have no impact on safety on motorways in the modelling.
Other impacts
No data related to other impacts was identified in the reports reviewed.
5.16. Bundle 6 – Cooperative Adaptive Cruise Control
Service Overview
Impacts
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A study carried out by TNO looking at the environmental benefits of C-V2X (TNO, 2020)
conducted a number of field tests on Dutch rural roads with vehicles equipped with CACC.
Platoons of 3 and 7 vehicles equipped with CACC and data logging systems drove in
regular traffic on a 2 lane rural road with controlled intersections. The logged data was
used to assess the CO2 emissions of the vehicles.
Traffic efficiency
No data was identified for this impact category in the report reviewed. It is assumed that
this service will not have an impact on traffic efficiency at an EU level.
Fuel consumption and CO2
The average reduction in CO2 emissions per vehicle was 6.0% for passenger vehicles. The
study noted that the field test produced varying impacts from just 1.8% reduction to 10.5%
reduction. For freight vehicles, the impact is around 20% higher than passenger cars,
resulting in a CO2 reduction of 7.2%. In absence of any further data, the same impacts have
been applied across all road types.
Environmental and emissions impacts
No data was identified for this impact category in the report reviewed. It is assumed that
this service will not have an impact on vehicle emissions at an EU level.
Safety
No data was identified for this impact category in the report reviewed. It is assumed that
this service will not have an impact on safety at an EU level.
5.17. Bundle 6 – Other
We recognise that Bundle 6 includes other critical services such as C-ITS cooperative
perception services and other services leading to higher levels of automation. However,
due to the early level of development of such services, there are no concrete studies that
have investigated the impacts under consideration in this IA and therefore these services
cannot be accurately represented in the model. This was confirmed during discussions with
stakeholders during the workshops, who agreed that there were no reliable sources, and
stated that the focus of the ITS Directive should be on increasing the deployment of
services with a higher level of maturity, rather than Bundle 6 services that are more forward
looking.
6. OVERLAP BETWEEN SERVICES
A number of ITS services covered in this assessment have similar functionality, therefore
the impact of certain services is likely to overlap. For example, a driver could be alerted to
an obstacle in the road through variable message signs using SRTI or through the vehicle
interface using V2V. Therefore, in practice, when two or more similar services are
deployed, certain impacts may not be additional and any further benefits may only be a
fraction of the services individual impact. It is therefore important to capture the interaction
between services, to avoid overestimating the benefits. Another consideration relates to
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overlaps between other legislation outside the ITS Directive framework, that play a role in
the deployment of ITS solutions, and the impacts arising from the services considered in
this assessment.
To this end, service overlap was accounted for in the assessment using a service weighting
matrix, as shown in Table 58. This matrix applies a percentage weighting from 0-100% to
each service, based on which services would be deployed before it in the progression of
the policy options. Weightings were applied in increments of 25%, in an attempt to account
for different amounts of overlap between different services. These were developed in the
context of the impact assessment support study and shared with stakeholders for
consultation. Within the C-ITS service bundles, the overlap between individual services
under each service type has already been accounted for using the values originally
developed in working groups under the C-ITS platform for the 2016 C-ITS Deployment
Study.
The full list of overlaps is described below:
 Multimodal travel information service: It is assumed that 100% of the impacts
would be eliminated due to MaaS on the basis that MaaS platforms include a travel
information service with the addition of a booking/reselling service.
 Travel information service: It is assumed that 75% of the impacts would be
eliminated due to RTTI on the basis that RTTI incorporates most aspects of travel
information services.
 Parking and pricing information: It is assumed that 25% of the impacts would
be eliminated due to RTTI on the basis that some navigation providers will already
be collecting this data as part of their service.
 Re-charging/re-fuelling location and pricing information: It is assumed that
50% of the impacts will be eliminated due to the provisions of AFIR in making
data available.
 Mobility management services: It is assumed that 75% of the fuel consumption,
emissions and traffic efficiency and 100% of safety impacts would be eliminated
due to traffic network management systems as the mobility management services
provide similar services but to the mobility system as a whole (rather than just the
road network).
 Road safety-related minimum universal traffic information service: It is
assumed that 50% of the impacts would be eliminated due to C-ITS services on the
basis that around half of the use cases utilise the same type of data (e.g. hazardous
location notification).
 S&S truck parking location information system: It is assumed that 100% of the
impacts would be eliminated due to S&S truck parking location reservation system
as the reservation system will incorporate all location information in the service.
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 All C-ITS service types (V2V, V2I motorway, V2I urban): It is assumed that
25% of the safety impacts would be eliminated due to traffic network management
systems on the basis that similar services are delivered to the end user through
different means. In the case of traffic network management systems it is through
VMS, and for C-ITS the service is delivered through in-vehicle systems.
Table 57: Service type and reference code
Service type Reference code
Multimodal travel information service (including linking between modes) 1_MMTIS-1
Multimodal travel information and booking/re-selling service (MaaS) 2_MaaS-1
Travel information service / Road traffic information & navigation services 3_Tinfo-1
Real-time traffic information service 4_RTTI-1
Parking (and pricing) information 5_Pinfo-1
Re-charging/re-fuelling location and pricing information 6_iFuel-1
(Enhanced) Traffic network and incident management systems 7_Tmang-2
Mobility management services 8_Mmang-2
Road safety-related minimum universal traffic information service 9_SRTI-3
S&S truck parking location information system 10_HDVPinfo-3
S&S truck parking location reservation system 11_HDVPres-3
C-ITS safety-based V2V services: 12_V2V-4
C-ITS V2I motorway focused applications: 13_V2Ihwy-5
C-ITS V2I urban only applications: 14_V2Iurb-5
Table 58: Service overlaps in percentages
Impact
1_M
MTI
S-1
2_
Ma
aS-
1
3_
Tin
fo-
1
4_
RT
TI-
1
5_
Pin
fo-
1
6_i
Fu
el-
1
7_T
ma
ng-
2
8_M
man
g-2
9_S
RT
I-3
10_H
DVPi
nfo-3
11_H
DVPr
es-3
12_
V2
V-4
13_V
2Ihw
y-5
14_
V2I
urb-
5
Fuel
consu
mption
0 100 25 100 75 50 100 25 50 0 100 100 100 100
CO 0 100 25 100 75 50 100 25 50 0 100 100 100 100
NOx 0 100 25 100 75 50 100 25 50 0 100 100 100 100
VOC 0 100 25 100 75 50 100 25 50 0 100 100 100 100
PM 0 100 25 100 75 50 100 25 50 0 100 100 100 100
Fataliti
es
0 100 25 100 75 50 100 0 50 0 100 75 75 75
Serious
injuries
0 100 25 100 75 50 100 0 50 0 100 75 75 75
Light
injuries
0 100 25 100 75 50 100 0 50 0 100 75 75 75
Materi
al
damag
es
0 100 25 100 75 50 100 0 50 0 100 75 75 75
Averag
e speed
0 100 25 100 75 50 100 25 50 0 100 100 100 100