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
Date: 2021-12-14
Institutions: Directorate-General for Mobility and Transport, European Commission
Subjects: combined transport, common transport policy, digital transformation, information system, intelligent transport system, road safety, road transport, sustainable mobility, systems interconnection, transport infrastructure

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}  
 
 
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 
Subsidiarity: Necessity of EU action ........................................................................................ 19 
3.2. 
Subsidiarity: Added value of EU action ................................................................................... 20 
3.3. 

4.  OBJECTIVES: WHAT IS TO BE ACHIEVED? ................................................................................ 20 

4.1.  General objectives .................................................................................................................... 20 
Specific objectives ................................................................................................................... 20 
4.2. 

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 
Proportionality.......................................................................................................................... 52 
7.4. 
Summary of comparison of options, including stakeholder views ........................................... 52 
7.5. 
Sensitivity analysis ................................................................................................................... 53 
7.6. 

8. 

PREFERRED OPTION ....................................................................................................................... 56 

i 

 
 
Policy option 3: Mandating provision of essential services ..................................................... 56 
8.1. 
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. 

4. 

CONSULTATION OF THE RSB ....................................................................................................... 59 

EVIDENCE, SOURCES AND QUALITY ......................................................................................... 59 

ANNEX 2: STAKEHOLDER CONSULTATION ....................................................................................... 61 

1. 

2. 

INTRODUCTION ............................................................................................................................... 61 

CONSULTATION METHODS ........................................................................................................... 62 

ANNEX 3: WHO IS AFFECTED AND HOW? ........................................................................................... 67 

1. 

2. 

PRACTICAL IMPLICATIONS OF THE INITIATIVE ..................................................................... 67 

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 
Emergency electronic brake light (EBL) ........................................................ 128 
Emergency vehicle approaching (EVA) ......................................................... 132 
Slow or stationary vehicle(s) warning (SSV) ................................................. 133 
Traffic jam ahead warning (TJW) .................................................................. 137 
Hazardous location notification (HLN) .......................................................... 142 
5.13.  Bundle 5 - C-ITS V2I motorway focused applications .......................................................... 146 
In-vehicle signage (VSGN) ............................................................................ 146 
In-vehicle speed limits (VSPD) ...................................................................... 148 
Probe Vehicle Data (PVD) ............................................................................. 152 
Roadworks warning (RWW) .......................................................................... 154 
Weather conditions (WTC)............................................................................. 157 
Shockwave damping (SWD) .......................................................................... 161 
5.14.  Bundle 5 - C-ITS V2I urban only applications ...................................................................... 162 

5.13.1. 
5.13.2. 
5.13.3. 
5.13.4. 
5.13.5. 
5.13.6. 

5.12.1. 
5.12.2. 
5.12.3. 
5.12.4. 
5.12.5. 

ii 

 
 
5.14.1. 
5.14.2. 
5.14.3. 

Green Light Optimal Speed Advisory (GLOSA) / Time to Green (TTG) ...... 162 
Signal violation/Intersection safety (SigV) ..................................................... 166 
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 

CAV 

CCAM 

CEF 

C-ITS 

CO2 

Day 1 

ASsessment of TRAnsport Strategies (modelling tool) 

Connected and Automated Vehicle 

Cooperative, Connected and Automated Mobility 

Connecting Europe Facility 

Cooperative Intelligent Transport System 

Carbon Dioxide 

Mature C-ITS services (deployed) 

Day 1.5 

Close to mature C-ITS services (partially deployed) 

Day 2 

Day 3 

eCall 

C-ITS services under development (not yet deployed) 

Future (automation support) C-ITS services 

Automated 112-based in-vehicle emergency call system 

EU CCMS 

EU C-ITS Security Credential Management System 

GDPR 

GLOSA 

IIA 

ITS 

KPI 

LNG 

MaaS 

MDM 

General Data Protection Regulation 

Green Light Optimal Speed Advisory 

Inception Impact Assessment 

Intelligent Transport System 

Key Performance Indicator 

Liquefied Natural Gas 

Mobility as a Service 

Multimodal Digital Mobility 

MMTIS 

Multi Modal Travel Information Service 

MS 

NAP 

NOx 

Member State 

National Access Point 

Nitrogen oxides 

iii 

 
 
OEM 

OPC 

PM 

PND 

PO 

PRM 

RSI 

RSU 

RTTI 

S&S 

SME 

SRTI 

SSMS 

SUMP 

TMC 

TRUST 

UVAR 

V2I 

V2V 

VMS 

VOC 

VRU 

Original Equipment Manufacturer 

Open Public Consultation 

Particulate Matter 

Personal Navigation Device 

Policy Option 

Person with Reduced Mobility 

Road Side Infrastructure (supporting ITS) 

Road Side Unit (supporting C-ITS) 

Real-Time Traffic Information 

Safe and secure 

Small or Medium Enterprise 

Safety Related Traffic Information 

Sustainable and Smart Mobility Strategy 

Sustainable Urban Mobility Plan 

Traffic management centre 

TRansport eUropean Simulation Tool (modelling tool) 

Urban Vehicle Access Restrictions 

Vehicle to Infrastructure  

Vehicle to Vehicle 

Variable Message Sign 

Volatile Organic Compound 

Vulnerable Road Users 

iv 

 
 
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 

1 

 
 
 
 
                                                 
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 

2 

 
 
 
 
                                                 
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 

I: 
Priority  area 
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 
freight 
and 
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 

3 

 
 
 
 
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  Regulation 18 and  on  C-ITS 19.  The  ITS 
Directive also has synergies with the new road safety policy framework for 2020-203020 and 
the  legislative  initiatives  on  vehicle  and  pedestrian  safety 21  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 

4 

 
 
 
 
 
                                                 
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  evaluation 26  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 

5 

 
 
 
 
                                                 
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.  
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. 
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. 
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 
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. 
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) 
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 
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 further develops the general and 
specific objectives of the directive 

Policy measures are defined to enlarge 
the scope and further strengthen 
investments in ITS and ensure the 
deployment of essential services. 

Policy measures are defined to further 
strengthen the coordination mechanisms 
and involvement of all ITS stakeholders 

Policy measures are defined to increase 
the availability of crucial data 

Policy measures are foreseen to increase 
the deployment of ITS and reach the 
scale needed to reap the (large) potential 
benefits 
Policy measures are foreseen to 
harmonize all reporting obligations and 
increase the use of KPIs 

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 

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 

6 

 
 
 
 
                                                 
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 

Lack of concertation and effective 
stakeholder coordination  

Limited data availability and access, lack 
of data quality and limited exchange and 
usage of data 

  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 

  Limited development of services such as MaaS 
and CCAM, leading to missed opportunities to 
build an inclusive multi-modal transport system 

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 

7 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                                 
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: 
road 
ITS 
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. 

the 
the 

IV:  Linking 
vehicle  with 
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 

8 

 
 
 
 
                                                 
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 

9 

 
 
 
 
 
                                                 
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 

10 

 
 
 
 
                                                 
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 

11 

 
 
 
 
 
                                                 
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 

12 

 
 
 
 
                                                 
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 

13 

 
 
 
 
 
                                                 
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 

14 

 
 
 
 
 
                                                 
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 

15 

 
 
 
 
                                                 
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 

16 

 
 
 
 
 
                                                 
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 

17 

 
 
 
 
                                                 
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 

18 

 
 
 
 
 
                                                 
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 

19 

 
 
 
 
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 

Increase 
deployment 

the 
and 

SO1:Increase  interoperability  and 
of 
cross-border 

continuity 

Indicator 
 

Increased  financial  and  administrative 
capacity to accelerated ITS deployment 

20 

 
 
 
 
General objective 
operational  use  of  ITS 
services across the EU, 
to improve road safety, 
increase  the  efficiency 
of the transport system 
as  a  whole  and  help 
transport 
linking  all 
foster  a 
to 
modes 
transport 
multimodal 
system  and,  and 
in 
doing so, to reduce the 
external 
negative 
effects of transport 

Specific objective 
applications,  systems  and  services 
supporting a common ITS market 

Indicator 
 

Increased  interoperability  and  continuity 
of services across Member States 

  Creation of common standards, principles 
and  quality  requirements  for  emerging 
ITS services 

 

Increased 
generated by all modes 

interoperability 

of 

data 

  Stronger  cooperation  in  ITS  governance, 

industry buy-in 

  Comparable  monitoring 
deployment across MSs 

of 

ITS 

  Solutions  for  (trust)  issues  with  data 

protection, privacy and liability  

 

Increased incentives / awareness to collect 
and share ITS data 

SO2: Establish a clear and effective 
concertation 
and 
coordination 
process  for  all  ITS  stakeholders 
(including stake-holders relevant in 
the  multimodal  context  of 
the 
Directive) 

improved 

SO3:  Ensure 
data 
availability,  access  and  quality 
standards  used  and  facilitate  the 
exchange  and  usage  of  data 
supporting ITS services 

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, 

21 

 
 
 
 
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. 

22 

 
 
 
 
                                                 
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. 

23 

 
 
 
 
                                                 
Table 5: ITS service bundles 

No. 

Service bundle 

ITS service type 

1a 

Information & 
booking services 
for travellers 

  Multimodal travel information service 

  Multimodal booking / re-selling 
service (including mobility as a 
service) 

Intended impacts on transport 

Improved trip planning choices 
(time/route/modal)76 leading to: 
  Congestion reduction / trip time 

  Reduction in fuel consumption / 

1b 

Information and 
booking services 
for drivers 

Travel 
management 
services 

Road safety and 
security 
applications 

2 

3 

4 

5 

6 

  Road traffic & navigation service 

emissions 

  Real-time traffic information service 

  Modal shift 

  Parking (and pricing) information  

  Reduction of transport costs 

  Re-charging/re-fuelling information  

 

Intermodal interfaces 

  Traffic incident management systems 

  Mobility management services 

(incl. external cost of transport 
to society) 

 

Improvement in resilience and 
quality of service 

  Road safety-related traffic information  

Improved transport safety  

  S&S truck parking  

 

eCall 

Vehicle-to-
vehicle (V2V) 

  C-ITS services such as electronic 
brake light & hazardous location 

Vehicle-to-
Infrastructure 
(V2I) 

  C-ITS services such as shockwave 

damping, in-vehicle speed limits, 
green light optimal speed advice and 
Signal violation 

  Reduction of accidents 
(fatalities and injuries) 

  Reduction of external costs 
(caused by accidents) 

  Congestion reduction / trip time 

  Reduction in fuel consumption / 

emissions 

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 

24 

 
 
 
 
 
                                                 
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. 

25 

 
 
 
 
 
                                                 
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 

Policy measure  Policy measure description 

Aim of the policy measure 

# 

Type of 
measure 

1 

Extensi
on of 
scope 

The scope of the Directive would be 
broadened to explicitly cover ITS 
services that support multimodal 
mobility.  

Adjust the 
scope of the 
Directive to 
explicitly 
include MDM 
services 

2 

MDM services 

The definition of the priority area 
would be broadened to ensure that it 
clearly covers services in support of 
multimodality. 

Update 
priority 
areas 

3 

4 

5 

6  New 
standard
s/ 
specific
ations 

7 

Enhanced 
traffic/mobility 
management 

The priority area would be updated by 
bringing together ‘mobility services’ 
and ‘traffic management’ under 
‘mobility management’.  

A new priority area would be 
established focusing on CCAM to be 
updated to reflect current needs.  

The scope of the application of the 
priority areas will be expanded from 
“standards and specifications” to also 
include ‘mandating data and services’.  

An extension of the validity of Article 
8 will be needed to reflect the new 
standardisation requirements. 

CCAM 

Include 
(mandatory) 
deployment in 
scope of 
application 

New 
standardisation 
mandate(s) 
under Article 8 

Revision of 
specification 
for RTTI 

Develop specifications for data types 
relevant for the delivery of essential 
RTTI services, including (1) UVAR; 

26 

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. 
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. 
Better reflect actions of transport 
authorities and prioritise the 
deployment of ITS infrastructure that 
supports mobility management more 
generally. 
Ensure that the subsequent actions 
relating to CCAM will be developed 
appropriately, accelerating 
deployment  
This will facilitate some of the policy 
measures below, which would help to 
ensure the deployment of ITS.  

This will enable the development of 
standards for new specifications, 
supporting the interoperability 
between different modes and for new 
services. 
Common specifications enable the 
development of interoperable 
datasets, support data exchange with 

SB 

1a 

1a 

2 

4-6 

All 

All 

1b 

 
 
 
 
SB 

1b 

1b 

4-6 

1b 

# 

Type of 
measure 

Policy measure  Policy measure description 

Aim of the policy measure 

(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. 
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). 

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 
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 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 

little transaction effort, foster service 
continuity and the faster/cheaper 
deployment of more comprehensive 
services. 

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. 

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. 

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. 

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 

Requirements 
for the access 
to in-vehicle 
generated data 
for road 
operation (asset 
and traffic 
management) 
services 

Standards for 
in-vehicle 
generated data 
for road 
operation (asset 
and traffic 
management) 
services 

Specifications 
for C-ITS (Day 
1, Day 1,5 and 
Day 2 services) 

8 

9 

10 

Mandate 
availability of 
crucial RTTI 
data 

11 

Mandati
ng data 
availabil
ity 

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 

27 

 
 
 
 
# 

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 
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. 
This mandate will oblige authorities 
and organisations responsible for the 
operation of the TEN-T 
comprehensive road network to 
deliver SRTI. 
This measure introduces a mandate 
for the delivery of C-ITS services in 
all new vehicle models after 2028. 

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. 
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. 
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. 
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 

28 

deployment of travel information 
services using these data. 

The measure applies to 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. 
Guaranteed deployment of SRTI 
services on TEN-T, possibly leading 
to spill-over effects on other parts of 
the network. 

3 

3 

The measure will accelerate the 
deployment of Day 1 C-ITS services. 

4 

All 

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 

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 

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. 

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 

13 

14 

15 

16 

17 

18 

Mandate 
availability of 
Safe & Secure 
truck parking 
data 

Mandate 
availability of 
(SRTI) services 

Mandate 
availability of 
Day 1 C-ITS 
services 

Mandati
ng 
services 

ITS 
deploy
ment 
principl
es 

Update the 
principles for 
specifications 
and 
deployment of 
ITS 

Governa
nce 
framew
ork 

Setting-up of 
governance and 
the facilitation 
of national & 
EU wide 
operational co-
ordination of 
NAPs 

Introduce legal 
provisions on 
governance of 
national & EU 
wide 
operational 
coordination of 
NAPs 

19 

Governa
nce 
framew
ork - C-
ITS 

Implement the 
European C-
ITS Trust 
model 

 
 
 
 
 
Policy measure  Policy measure description 

Aim of the policy measure 

# 

Type of 
measure 

20 

21 

Governa
nce 
framew
ork 

Introduce legal 
provisions on 
the EU C-ITS 
Trust model 

Further 
improve and 
streamline the 
interaction with 
ITS 
stakeholders 

applications. 
Give the EU CCMS legal status. This 
certificate policy defines requirements 
for the management of public key 
certificates for C-ITS applications. 
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) 

22 

23 

24 

25 

Update and 
streamline 
reporting 
obligations 

Improve 
reportin
g 

Mandate 
reporting based 
on common 
format & KPIs 

Enhance 
coheren
ce 

Improve the 
coherence of 
the ITS 
Directive with 
the existing 
legal 
framework 

Improve the 
coherence of 
the ITS 
Directive with 
expected 
initiatives 

Streamline reporting requirements, 
with reporting for all delegated acts 
integrated into Member States’ 
overall reporting on the Directive.  
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. 

The approach taken in relation to ITS 
services will be aligned with: 

  GDPR 

 

ePrivacy legislation 

  Passenger rights legislation 

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 

Providing legal and technical 
certainty to the C-ITS trust model will 
accelerate the development and 
deployment of C-ITS services.  
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.  
This will reduce administrative 
burden, particularly for Member 
States.  

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. 
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. 
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.  

SB 

4-6 

All 

All 

All 

All 

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).  

29 

 
 
 
 
 
Figure 8: stakeholder support for measures addressing SO1 

Figure 9: stakeholder support for measures addressing SO2 

30 

 
 
 
 
 
 
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. 

31 

 
 
 
 
 
                                                 
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. 

32 

 
 
 
 
 
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 
1  Adjust the scope of the Directive to explicitly include MDM services 
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 

SO1  SO2  SO3  PO1 PO2 PO3 
     
     
     
     
     
     

     

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  

     
     

     

1
O
P

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 
in-vehicle  data 

initiatives  (i.e.  Mobility  Data  Space, 

expected 
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) 

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  

     

     
     
     

2
O
P

     

9  Standards  for  in-vehicle  generated  data  for  road  operation  (asset  and 



traffic management) services 

14  Mandate availability of SRTI services 
15  Mandate availability of Day 1 C-ITS services 

    

     
     

3
O
P

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. 

33 

 
 
 
 
 
 
 
 
 
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 

34 

 
 
 
 
 
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 

35 

 
 
 
 
                                                 
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". 

36 

 
 
 
 
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 

New vehicles equipped 

Baseline 

PO 1 

PO 2 

PO 3 

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 

New infrastructure (RSU) 

New infrastructure (RSI) 

New infrastructure (TMC) 

Source: Ricardo et al. (2021) 

196,733,092  256,148,549  341,479,678  392,837,099 

20,250 

22,117 

115 

45,599 

32,940 

159 

45,599 

186,247 

402 

155,552 

196,344 

425 

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 

Public 

Roadside units 
Roadside infrastructure 
National access points 
Central ITS sub-systems 

0.2 
6.0 
0.7 
1.0 

PO1 
Total  Net 
0.2 
0.4 
0.9 
6.9 
0.1 
0.8 
0.1 
1.1 

PO2 
Total  Net 
0.2 
0.4 
3.2 
9.2 
0.4 
1.1 
0.6 
1.6 

PO3 
Total  Net 
1.1 
1.3 
3.3 
9.3 
0.4 
1.1 
0.6 
1.6 

83 https://op.europa.eu/en/publication-detail/-/publication/043ee22b-643b-11eb-aeb5-01aa75ed71a1 

37 

 
 
 
 
                                                 
Sector 

Cost component 

Baseline 

Private 

Total infrastructure 
In-vehicle systems 
Smartphone and applications 

Total mobile equipment 

7.8 
16.3 
0.0 

16.4 

PO1 
Total  Net 

PO2 
Total  Net 

PO3 
Total  Net 

9.2 
22.5 
0.01 

22.5 

1.3 
6.2 
0.01 

6.2 

12.3 
22.5 
0.02 

22.5 

4.4 
6.2 
0.02 

6.2 

13.2 
31.8 
0.02 

31.8 

5.3 
15.4 
0.02 

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 

38 

 
 
 
 
 
 
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 

39 

 
 
 
 
 
                                                 
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 

Cost category 
Travel time 

Baseline 
6,164.0 
Source: ASTRA / TRUST model 

PV 2021-2040 relative to baseline 

PO1 
-43.0  

PO2 
-138.8  

PO3 
-144.5  

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 

Year  Mode 

2030 

2040 

Annual fuel consumption in 2030 
Saving relative to the baseline in 2030 
% savings relative to the baseline 
Annual fuel consumption in 2040 
Saving relative to the baseline in 2040 
% savings relative to the baseline 

Baseline 
202 
- 
- 
123.6 
- 

PO1 
201.8 
0.19 
-0.10% 
123.4 
0.2 
-0.16% 

PO2 
201.1 
0.85 
-0.42% 
123.2 
0.42 
-0.34% 

PO3 
201 
0.92 
-0.46% 
122.8 
0.77 
-0.62% 

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 

Cost category 
Fuel consumption 

Baseline 
790.0 

Source: ASTRA / TRUST model 

PV relative to baseline 

PO1 
-0.6 

PO2 
-2.1 

PO3 
-2.4  

85 The monetary value was calculated based on the cost of time values from the 2019 Handbook of External 

Costs of Transport 

40 

 
 
 
 
 
 
 
 
 
                                                 
 
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 

2030 

Freight transport (billion tkm/year) 
Transport activity 
% difference 
Transport activity 
% difference 
Source: ASTRA / TRUST model 

2040 

Baseline 
2,898 
- 
3,149 
- 

PO1 
2,898 
0.00% 
3,149 
0.02% 

PO2 
2,899 
0.03% 
3,152 
0.09% 

PO3 
2,899 
0.03% 
3,152 
0.09% 

Table 15: Modal split for passengers 

Year 
2030 

2040 

Mode 
Car 
Bus 
Train 
Car 
Bus 
Train 

Baseline 
80.2% 
9.4% 
10.5% 
79.9% 
9.0% 
11.1% 

PO1 
0.1% 
0.0% 
0.0% 
0.1% 
0.0% 
-0.1% 

PO2 
0.3% 
-0.2% 
-0.1% 
0.4% 
-0.2% 
-0.2% 

PO3 
0.3% 
-0.2% 
-0.1% 
0.3% 
-0.1% 
-0.2% 

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 

2030 

2040 

Increase (EUR bn) 

% difference to the baseline 

Increase (EUR bn) 

% difference to the baseline 

Source: ASTRA / TRUST model 

PO1 
1.5 

0.01% 

4.3 

0.03% 

PO2 
8.6 

0.07% 

16.2 

0.11% 

PO3 
8.9 

0.07% 

17.3 

0.12% 

41 

 
 
 
 
 
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 

42 

 
 
 
 
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 
Serious injuries 
Minor injuries 
PO1 
Fatalities 
Serious injuries 
Minor injuries 
PO2 
Fatalities 
Serious injuries 
Minor injuries 
PO3 
Fatalities 
Serious injuries 
Minor injuries 

 18,347  
 247,699  
 863,934  

 -  
 -  
 -  

 18,315  
 247,291  
 862,752  

 18,244  
 246,709  
 861,624  

 18,195  
 246,069  
 859,477  

 32  
 407  
 1,182  

 104  
 990  
 2,310  

 152  
 1,629  
 4,457  

 -  
 -  
 -  

0.2% 
0.2% 
0.1% 

0.6% 
0.4% 
0.3% 

0.8% 
0.7% 
0.5% 

 16,655  
 224,654  
 799,892  

 -  
 -  
 -  

 16,496  
 222,475  
 792,729  

 16,400  
 221,611  
 791,002  

 15,898  
 214,735  
 767,363  

 159  
 2,179  
 7,163  

 255  
 3,043  
 8,890  

 757  
 9,919  
 32,529  

 -  
 -  
 -  

1.0% 
1.0% 
0.9% 

1.5% 
1.4% 
1.1% 

4.5% 
4.4% 
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 
1.8  

% difference 
to baseline 
0.25% 

Difference 
to baseline 
4.0  

% difference 
to baseline 
0.55% 

Difference 
to baseline 
8.5  

% difference 
to baseline 
1.16% 

Fatalities 

43 

 
 
 
 
  
 
 
Difference 
to baseline 

Serious injuries  3.9  
1.0  
Minor injuries 

PO1 

PO2 

PO3 

% difference 
to baseline 
0.25% 
0.22% 

Difference 
to baseline 
7.0  
1.4  

% difference 
to baseline 
0.44% 
0.32% 

Difference 
to baseline 
17.0  
4.1  

% difference 
to baseline 
1.06% 
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 

2030 

2040 

Baseline 

PO1 

Annual transport expenditure per person 

€ 801 

% difference to the baseline 

- 

Annual transport expenditure per person 

€ 715 

% difference to the baseline 

- 

€ 800 

0.2% 

€ 713 

0.3% 

PO2 

€ 796 

0.7% 

€ 709 

0.9% 

PO3 

€ 796 

0.7% 

€ 709 

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. 

44 

 
 
 
 
 
 
 
                                                 
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 
Direct average employment (FTEs) 
2025-2030 
2031-2035 

1,800 – 2,400 
2,000 – 2,800 

PO2 

PO3 

2,500 – 3,500 
3,000 – 4,100 

5,400 – 7,500 
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. 

45 

 
 
 
 
                                                 
PO1 
1,300 – 1,800 

Period 
2036-2040 
Total average employment (FTEs) 
2025-2030 
2031-2035 
2036-2040 

6,800 – 9,500 
7,800 – 10,800 
5,000 – 7,000 

PO2 
1,800 – 2,500 

10,190 – 14,200 
12,000 – 16,600 
7,400 – 10,200 

PO3 
2,300 – 3,200 

21,200 – 29,500 
15,300 – 21,300 
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 

2030 

2040 

Annual CO2 emissions in 2030 
Saving relative to the baseline in 2030 
% savings relative to the baseline 
Annual CO2 emissions in 2040 
Saving relative to the baseline in 2040 

Baseline 
522.6 
- 
- 
168.9 
- 

PO1 
522.1  
0.6  
0.10% 
168.4  
0.5  

PO2 
520.2  
2.5  
0.50% 
167.7 
1.2  

PO3 
520.0  
2.7  
0.50% 
167.0 
1.9  

46 

 
 
 
 
% savings relative to the baseline 

- 

0.30% 

0.70% 

1.10% 

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 
Annual 
emissions  

Saving  relative  to 
the baseline  

%  difference  to 
the baseline 

2040 
Annual 
emissions  

Saving  relative 
to the baseline  

%  difference  to 
the baseline 

50,447 

Baseline 
PM 
NOx   885,687 
VOC  67,457 

50,384 

PO1 
PM 
NOx   884,940 
VOC  67,475 

50,425 

PO2 
PM 
NOx   884,136 
VOC  67,568 

- 
- 
- 

63 
747 
-18 

23 
1,550 
-111 

50,429 

PO3 
PM 
NOx   884,018 
VOC  67,558 
Source: Ricardo et al. (2021) 

18 
1,669 
-101 

- 
- 
- 

0.13% 
0.08% 
-0.03% 

0.05% 
0.18% 
-0.16% 

0.04% 
0.19% 
-0.15% 

15,050 
308,373 
37,059 

14,998 
307,733 
37,048 

15,007 
307,349 
37,070 

15,027 
307,108 
37,051 

- 
- 
- 

53 
640 
11 

43 
1,024 
-11 

24 
1,265 
8 

- 
- 
- 

0.35% 
0.21% 
0.03% 

0.29% 
0.33% 
-0.03% 

0.16% 
0.41% 
0.02% 

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 

47 

 
 
 
 
  
                                                 
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 

NOx  

VOC 

1,000 

13,140 

-69 

11.0  

158.2  

-0.1  

Total 

14,070 
Source: Ricardo et al. (2021) 

169.1  

485 

22,038 

-1,301 

21,222 

4.4  

223.3  

-1.3  

226.4  

314 

25,005 

-1,001 

24,319 

2.8  

253.1  

-1.1  

254.8  

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 

48 

 
 
 
 
  
 
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 

PO1 

Indicator 
PO2 
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 

PO3 

In  2040,  145mn  equipped 
vehicles, 
smart-
111mn 
phone users of ITS services, 
45k RSUs + 33k RSI + 159 
TMCs 

In  2040,  145mn  equipped 
vehicles,  196mn 
smart-
ITS 
phone  users 
services,  45k  RSU,  153k 
RSIs, 402 TMCs 

of 

In  2040,  200mn  equipped 
vehicles,  193mn 
smart-
ITS 
phone 
services, 156k RSUs, 196k 
RSIs, 425 TMCs 

users 

of 

financial 
administrative 
to 
ITS 

Increased  coherence  with 
other 
and 
legislation 
requirements 
for  B2G 
access to in-vehicle data 

Specific  objective  1:  Increase  interoperability  and  cross-border  continuity  of  ITS  applications,  systems  and 
services supporting a common ITS market 
Increased 
and 
capacity 
accelerated 
deployment 
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 

Service  mandates 
administrative 
increases 

Data  mandates 
administrative 
increases 

in-vehicle 
road 
for 
service 
essential 

impose 
capacity 

impose 
capacity 

Include 
deployment 
mandates  (data  &  services) 
in  scope  of  the  Directive 
(using 
common 
specifications) 
Include 
deployment 
mandates  (data  &  services) 
in  scope  of  the  Directive 
(using 
common 
specifications) 

Standards 
for 
generated  data 
+ 
operation 
mandates 
for 
services 
Standards 
for 
generated  data 
operation 

with 

Same as PO2 

in-vehicle 
road 
for 

deployment 
Include 
mandates 
for  data  and 
services  in  scope  of  the 
Directive 

Updates  of  priority  areas, 
for  B2G 
requirements 
access  to  in-vehicle  data, 
for  C-ITS, 
specifications 
coherence 
other 
legislation 
Updates of priority areas 

Creation  of  common 
standards,  principles 
quality 
and 
requirements 
for 
emerging 
ITS 
services 
Increased 
interoperability 
of 
data  generated  by  all 
modes 
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 
Comparable 
monitoring  of 
deployment 
MSs 
Specific objective 3: Ensure  improved data availability, access and quality  standards used and facilitate the 
exchange and usage of data supporting ITS services 
Increased  coherence  with 
Solutions  for  (trust) 
other 
and 
legislation 
data 
issues  with 
initiatives such as TEN-T + 
protection, 
privacy 
legal  provisions  on  C-ITS 
and liability  
trust model 

Further 
and 
streamline  interaction  with 
ITS stakeholders 
Streamline 
reporting 
obligations  and  mandate 
common format & KPIs 

Legal  provisions  on  EU-
wide coordination of NAPs 

ITS 
across 

Same as PO2 

Same as PO1 

Same as PO1 

Same as PO1 

Same as PO1 

improve 

49 

 
 
 
 
Indicator 
Increased incentives / 
awareness  to  collect 
and share ITS data 

PO1 
Update 
principles 
coherence 
initiatives 

deployment 
increased 
other 

+ 
with 

PO2 
Multiple  data  mandates 
ensure data collection 

PO3 
Multiple  service  mandates 
ensure data collection 

Societal, economic and environmental benefits (all monetary values in present value 2021-2040) 
Fuel consumption 

CO2 emissions 

Pollutant emissions – 
PM, NOx, VOC  
Accidents 

Limited 
0.16% 
impact. 
reduction in 2040 or -0.6bn€ 
compared to the baseline 
Limited 
0.30% 
impact. 
reduction in 2040 or -0.6bn€ 
compared to the baseline 
Limited,  0.17bn€  reduction 
compared to the baseline 
Limited,  0.9%  reduction  in 
2040  or  -6.7bn€  compared 
to the baseline 

Travel time 

Moderate, 
43.0bn€ 
reduction  compared  to  the 
baseline 

Positive 
0.34% 
impact. 
reduction in 2040 or -2.1bn€ 
compared to the baseline 
Positive 
0.70% 
impact. 
reduction in 2040 or -2.1bn€ 
compared to the baseline 
Limited,  0.23bn€  reduction 
compared to the baseline 
impact,  1.1% 
Moderate 
reduction 
in  2040  or  -
12.3bn€  compared  to  the 
baseline 
Very  positive,  138,8bn€ 
reduction  compared  to  the 
baseline 

Very positive impact. 0.62% 
reduction in 2040 or -2.4bn€ 
compared to the baseline 
Very positive impact. 1.10% 
reduction in 2040 or -2.4bn€ 
compared to the baseline 
Limited  0,25bn€  reduction 
compared to the baseline 
4.1% 
Very 
reduction 
in  2040  or  -
29.5bn€  compared  to  the 
baseline 
Very  positive,  144,5bn€ 
reduction  compared  to  the 
baseline 

positive. 

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 

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 

PO1 
+ 

PO2 
+++ 

PO3 
++++ 

++ 

++(+)  ++(+) 

+ 

+ 

+++ 

++++ 

+++ 

++++ 

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). 

50 

 
 
 
 
 
  
 
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) 

Roadside units 
Roadside infrastructure 
National access points 
Central ITS sub-systems 
In-vehicle systems 
Smartphone and applications 

Total Costs  

Reduction in external costs of accidents 
Time saved  
Reduction in external costs of CO2 emissions 
Reduction in external costs of air pollutants 
Fuel saving  

Total Benefits  

Total Net Benefits  

Benefit/Cost ratio 

Source: Ricardo et al. (2021) 

PO1 
0.2 
0.9 
0.1 
0.1 
6.2 
0.0 

7.5 

6.7 
43.0 
0.6 
0.2 
0.6 

51.1 

43.6 

6.8 

PO2 
0.2 
3.2 
0.4 
0.6 
6.2 
0.0 

10.6 

12.3 
138.8 
2.1 
0.2 
2.1 

155.5 

144.9 

14.7 

PO3 
1.1 
3.3 
0.4 
0.6 
15.4 
0.0 

20.8 

29.5 
144.5 
2.4 
0.3 
2.4 

179.1 

158.3 

8.6 

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 

51 

 
 
 
 
  
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 

ITS Directive 
Transport policies (e.g. Smart and Sustainable Mobility Strategy, Vision Zero) 
GDPR, E-privacy & EECC proposals 

Overall coherence 

PO1 
+ 
+ 
+ 

PO2  PO3 
+++ 
++ 
+++ 
++ 
+ 
+ 

+ 

++ 

+++ 

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 

52 

 
 
 
 
  
 
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. 

53 

 
 
 
 
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 

Short 

Long 

Short 

Low sensitivity 

High sensitivity 

Long 
Source: Ricardo et al. (2021) 

3% 

1.5% 

6% 

3% 

3% 

1.5% 

6% 

3% 

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 

54 

 
 
 
 
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 

Year 
2030 

2040 

Mode 
Car 
Bus 
Train 
Car 
Bus 
Train 

Baseline 
80.2% 
9.4% 
10.5% 
79.9% 
9.0% 
11.1% 

Source: ASTRA / TRUST model 

PO1 
80.2% 
9.4% 
10.4% 
80.0% 
8.9% 
11.1% 

PO2 
80.5% 
9.2% 
10.3% 
80.3% 
8.8% 
10.9% 

PO3 
80.5% 
9.2% 
10.3% 
80.2% 
8.8% 
10.9% 

PO3 low 
80.3% 
9.3% 
10.4% 
80.0% 
9.0% 
11.0% 

PO3 high 
80.0% 
9.5% 
10.5% 
79.7% 
9.2% 
11.2% 

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 

Roadside units 
Roadside infrastructure 
National access points 
Central ITS sub-systems 
In-vehicle systems 
Smartphone & applications 

Total costs  

Accident reduction benefits 
Time saved benefits 
CO2 emission benefits 
Other emissions benefits 
Fuel saving benefits 

Total benefits  
Total net benefits  
Benefit/Cost ratio 

Source: ASTRA / TRUST 

PO3 - 
Difference 
relative to 
the baseline 
1.1  
3.3  
0.4  
0.6 
15.4  
0.0  
20.8  
29.5  
144.5  
2.4  
0.3  
2.4  
179.1  
158.3  
8.6 

PO3 - sensitivity low 

PO3 - sensitivity high 

% change to 
PO3 

0% 
0% 
0% 
0% 
0% 
0% 
0% 
9% 
12% 
15% 
40% 
15% 
11% 
13% 
n/a 

Difference 
relative to 
the baseline 
1.1  
3.3  
0.4  
0.6  
15.4  
0.0  
20.8  
42.8  
194.6  
4.1  
0.7  
4.1  
246.3  
225.5  
11.8 

% change to 
PO3 

0% 
0% 
0% 
0% 
0% 
0% 
0% 
45% 
35% 
69% 
179% 
69% 
38% 
42% 
n/a 

Difference 
relative to the 
baseline 
1.1  
3.3  
0.4  
0.6 
15.4  
0.0  
20.8  
32.3  
161.2  
2.8  
0.4  
2.8  
199.4  
178.6  
9.6 

55 

 
 
 
 
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  required 89 .  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  Point 91 .  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. 

56 

 
 
 
 
                                                 
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  
roadside infrastructure  3.3  
National access points  0.4  
central ITS sub-systems  0.6 

In-vehicle systems  15.4  

Smartphone and applications  0.0  
Total costs  20.8 
Total Benefits  179.1  
158.3 
8.62 

Total net benefits 
Benefit/Cost ratio 

8.  PREFERRED OPTION 

1.7  
4.9  
0.6  
0.9  
23.1  
0.0  
31.2  
179.1 
147.9 
5.75 

2.2  
6.5  
0.8  
1.2  
23.1  
0.0  
33.8  
179.1  
145.3  
5.29 

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. 

57 

 
 
 
 
  
 
                                                 
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 

Mandate  reporting  based  on  common  format  & 
KPIs 
Improve the coherence of the ITS Directive with 
the existing legal framework (e.g. GDPR) 
Improve the coherence of the ITS Directive with 
expected initiatives (e.g. TEN-T Regulation) 

Not 
quantified 
Not 
quantified 
Not 
quantified 
Not 
quantified 

Recurrently  reduces  administrative  costs  of 
Member States 
Recurrently  reduces  administrative  costs  of 
Member States 
Reduces administrative and compliance costs of 
all stakeholders that deploy ITS services 
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. 

interoperability 

Specific objective 
Increase 
and 
cross-border  continuity  of  ITS 
applications, systems and services 
supporting a common ITS market  

Establish  a  clear  and  effective 
concertation 
and 
coordination 

Progress indicators 
  KPIs95 on the deployment of ITS services, 

including services mandated by the proposal. 

  Qualitative  assessment  of  the  ITS  activities  of 

public and private stakeholders. 

Source of data 

  Member 

State reports 

  CEF-funded 
projects 

  Number of meetings and level of participation 

  Commission 

from all public and private stakeholder categories. 

95 List of KPIs available on https://ec.europa.eu/transport/themes/its/road/action_plan/its_national_reports_en 

58 

 
 
 
 
                                                 
Specific objective 
process  for  all  ITS  stakeholders 
(including 
multimodal 
the 
context) 
Ensure improved data availability, 
access  and  quality  standards  to 
facilitate  the  exchange  and  usage 
of data supporting ITS services 

Progress indicators 

Source of data 

  Number of coordination projects (CEF, DEP) and 

participating stakeholders 

  KPIs for data availability and accessibility on 

  Member 

NAPS, including mandated data. 

State reports 

  Qualitative assessment of the ITS activities of 

public and private stakeholders. 
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. 

59 

 
 
 
 
 
 
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  2021 96 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 

60 

 
 
 
 
                                                 
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. 

61 

 
 
 
 
 
 
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 

62 

 
 
 
 
                                                 
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 

63 

 
 
 
 
 
                                                 
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 
origin 

Belgium 

Germany 

France 

Sweden  

Finland 

Austria 

Italy 

Netherlands 

Czechia 

Spain 

of 

Number 
responses 

of 

% of responses  Country of origin  Number 

of 

responses 

% 
responses 

of 

38 

29 

21 

11 

8 

7 

6 

5 

4 

4 

25.5% 

19.5% 

14.1% 

7.4% 

5.4% 

4.7% 

4% 

3.4% 

2.7% 

2.7% 

Poland 

Greece 

Ireland 

Luxembourg 

Denmark 

Malta 

Norway 

Switzerland 

Israel 

China 

4 

2 

2 

1 

1 

1 

1 

1 

1 

1 

2.7% 

1.3% 

1.3% 

0.7% 

0.7% 

0.7% 

0.7% 

0.7% 

0.7% 

0.7% 

Figure 17: Classification and number of stakeholders responding to the OPC 

Stakeholder group 

Number of responses 

% of responses 

Academic/research institution 

Business association 

Company/business organisation 

Environmental organisation 

Consumer organisation 

EU citizen 

Non-governmental organisation 

Public authority 

Trade union 

3 

37 

46 

1 

3 

12 

12 

22 

1 

2% 

24.8% 

30.9% 

0.7% 

2% 

8.1% 

8.1% 

14.8% 

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 

64 

 
 
 
 
 
                                                 
Stakeholder group 

Other 

Number of responses 

% of responses 

11 

7.4% 

Targeted consultation  

The following key and relevant stakeholder groups were targeted:  

  EU  Public  bodies  (including  European 
international organisations and public banks). 

institutions,  standardisation  bodies, 

  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 

65 

 
 
 
 
 
                                                 
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 

Public  authorities  and 
other public bodies 

5 (+1 exploratory) 

18 (+2 exploratory) 

Industry and associations 

23 (+3 exploratory) 

Civic society 

TOTAL  

7 

59 

Stakeholder workshops 

3 

10 

19 

4 

36 

66 

8 

27 

40 

11 

86 

 
 
 
 
 
A series of six workshops were organised to support the impact assessment. 

Workshop 

Date 

Objectives 

Type of workshop 

No.  of  registered 
participants 

1 

2 

3 

4 

5 

6 

15 
Decembe
r 2020 

  Overview  of  proposed  study, 

including methodology 
  Overview of IIA responses 
  Discussion  on  definition  of  main 

for 

Open 
interested 
stakeholders 

all 

285 

problems 

14 
January 
2021 

19 
January 
2021 

  Validation  of  key  data  and 
assumptions  related  to  specific 
technical 
problem  areas  with 
experts 

Restricted 
to 
stakeholders/experts 
technical 
with 
background 

a 

  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 

18 

26 

310 

25 

Open  with  separate 
sessions  restricted  to 
selected  participants 
identified from initial 
registration 

Restricted 
to 
stakeholders  with  an 
expertise 
in  policy 
assessments 

all 

202 

for 

Open 
interested 
stakeholders 

3  March 
2021 

  Overview of study progress to date 
  Summary of OPC responses  
  Presentation  and  discussion  on 

proposed policy options  

14  April 
2021 

June 

24 
2021 

  Presentation  of 

the  high-level 
impact assessment methodology to 
validate intervention logic and key 
assumptions 

  Gathering 

  Presentation  of  the  draft  final 
results from the impact assessment 
the 
feedback 
preferred  policy  option,  including 
on  legal,  political  and  technical 
feasibility to inform the final report 

on 

67 

 
 
 
 
 
 
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 

Direct benefits 

Amount 

Comments 

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 

68 

 
 
I. Overview of Benefits (total for all provisions) – Preferred Option 

Description 

Amount 

Comments 

(i.e.  present  value  2021-
2040) 

of 

Reduction 
fuel 
consumption (i.e. present 
value 2021-2040) 

€2.4 billion 

Indirect benefits 
Reduction  of  external 
road 
costs 
safety  (i.e.  present  value 
2021-2040) 

related 

to 

€29.5 billion 

€2.4 billion 

related 

Reduction  of  external 
costs 
to  CO2 
emissions  relative  to  the 
baseline 
(i.e.  present 
value 2021-2040) 

€0.3 billion 

to 

related 

Reduction  of  external 
costs 
air 
emissions 
pollution 
relative  to  the  baseline 
(i.e.  present  value  over 
2021-2040) 
Innovation 
competitiveness 
mobility sector 

/ 
the 

in 

(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. 

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 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. 
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. 
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. 
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 

69 

 
 
 
 
 
 
 
 
 
 
 
II. Overview of costs – Preferred option 

Citizens/ 
Consumers  

Businesses 

Administrations 

One-
off 

Re-
current 

One-
off 

Re- 
current 

One-off 

Recurrent 

infrastructure 
support 
of 
services 

in 
ITS 

Compliance 
related 
to 
equipment 
vehicles 
dedicated 
equipment 
support 
services 

of 

costs 
the 
of 
with 

in 
ITS 

Administrative 
costs  related  to  the 
digitalisation 
of 
transport 
public 
data and monitoring 
costs 

€2.9 bn 

National access points: €0.4 bn 

NAP: 
<€0.1 bn 

Direct 
costs 

€10.5 
bn 

€4.9 
bn 

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, 
reporting 
common 
format  supported  by  common 
reporting  KPIs  and  alignment  of 
(from 
reporting 
Delegated 
and 
Directive)  will  simplify  overall 
reporting under the Directive. 

requirements 
Regulations 

70 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  

71 

 
 
 
 
                                                 
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  

72 

 
 
 
 
                                                 
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. 

73 

 
 
 
 
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 

74 

 
 
 
 
                                                 
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 

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) 

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  

Bundle 2: Travel 
management 
services 

 

(Enhanced) Traffic network and 
incident management systems 

  Mobility management services 

Bundle 3: Road 
safety and 
security 
(excluding C-
ITS) 

 

 

 

SRTI service 

S&S truck parking location information 
and reservation system 

eCall (current scope only) 

Service end-
users 

Active modes, 
micro mobility, 
public transport, 
car users, taxis  

Car users, public 
transport, taxis, 
trucks  

ITS services focused on 
providing dynamic travel 
information and booking 
services to support journeys 
carried out by travellers. 

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. 

ITS services supporting 
mobility, network and traffic 
management by road operators 
and transport authorities.  

Car users, trucks, 
taxis, public 
transport (active 
modes) 

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 

Bundle 5: 
Vehicle-to-
Infrastructure 
(V2I) C-ITS 

Bundle 6: Future 
C-ITS services 

  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  

  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 

  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 

75 

 
 
 
 
 
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 

France 
Netherlands 
Slovenia 
Finland 
Czech Republic 
Austria 
Germany 
Sweden 
Belgium 
Denmark 
Spain 

ITS 
projects 
13 
4 
3 
2 
9 
8 
16 
5 
15 
6 
10 

NAP 
Status 
3 
10 
10 
6 
10 
3 
3 
10 
16 
10 
10 

ITS L2 & L3 
deployment 
2 
2 
5 
10 
5 
17 
6 
12 
4 
14 
9 

C-ITS 
deployment 
2 
4 
6 
9 
5 
3 
8 
7 
1 
11 
15 

Total 
score 
20 
20 
24 
27 
29 
31 
33 
34 
36 
41 
44 

Grouping 

Front Runner 
Front Runner 
Front Runner 
Front Runner 
Front Runner 
Front Runner 
Front Runner 
Front Runner 
Planned Adopter 
Planned Adopter 
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. 

76 

 
 
 
 
                                                 
Country 

Luxembourg 
Italy 
Portugal 
Greece 
Hungary 
Estonia 
Croatia 
Lithuania 
Poland 
Ireland 
Malta 
Romania 
Bulgaria 
Cyprus 
Latvia 
Slovak Republic 

ITS 
projects 
1 
18 
11 
7 
26 
26 
12 
26 
21 
26 
26 
17 
19 
26 
26 
26 

NAP 
Status 
3 
3 
25 
17 
10 
14 
19 
19 
19 
14 
26 
23 
21 
21 
24 
26 

ITS L2 & L3 
deployment 
20 
19 
10 
17 
15 
13 
24 
11 
16 
18 
7 
24 
24 
24 
24 
24 

C-ITS 
deployment 
24 
14 
10 
17 
12 
24 
24 
24 
24 
24 
24 
24 
24 
24 
24 
24 

Total 
score 
48 
54 
56 
58 
63 
78 
79 
80 
80 
83 
83 
88 
89 
96 
98 
100 

Grouping 

Planned Adopter 
Planned Adopter 
Planned Adopter 
Planned Adopter 
Planned Adopter 
Follower 
Follower 
Follower 
Follower 
Follower 
Follower 
Follower 
Follower 
Follower 
Follower 
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 

77 

 
 
 
 
 
 
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. 

78 

 
 
 
 
                                                 
2.  BASELINE SCENARIO 

to  reflect 

the  fundamental  socio-economic, 

transport  and  GHG  emissions.  The  socio-economic  and 

technological  and  policy 
In  order 
developments,  the  Commission  prepares  periodically  an  EU  Reference  Scenario  on 
energy, 
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 

EU27 
Austria 
Belgium 
Bulgaria 
Croatia 
Cyprus 
Czechia 
Denmark 
Estonia 
Finland 
France 
Germany 
Greece 
Hungary 
Ireland 
Italy 
Latvia 
Lithuania 
Luxembourg 
Malta 
Netherlands 
Poland 
Portugal 
Romania 
Slovakia 
Slovenia 
Spain 
Sweden 

2020 
447.7 
8.90 
11.51 
6.95 
4.06 
0.89 
10.69 
5.81 
1.33 
5.53 
67.20 
83.14 
10.70 
9.77 
4.97 
60.29 
1.91 
2.79 
0.63 
0.51 
17.40 
37.94 
10.29 
19.28 
5.46 
2.10 
47.32 
10.32 

Population 
2025 
449.3 
9.03 
11.66 
6.69 
3.94 
0.93 
10.79 
5.88 
1.32 
5.54 
68.04 
83.48 
10.51 
9.70 
5.27 
60.09 
1.82 
2.71 
0.66 
0.56 
17.75 
37.57 
10.22 
18.51 
5.47 
2.11 
48.31 
10.75 

2030 
449.1 
9.15 
11.76 
6.45 
3.83 
0.96 
10.76 
5.96 
1.31 
5.52 
68.75 
83.45 
10.30 
9.62 
5.50 
59.94 
1.71 
2.58 
0.69 
0.59 
17.97 
37.02 
10.09 
17.81 
5.44 
2.11 
48.75 
11.10 

GDP growth 

2020-‘25 
0.9% 
0.9% 
0.8% 
0.7% 
0.2% 
0.7% 
1.6% 
2.0% 
2.2% 
0.6% 
0.7% 
0.8% 
0.7% 
1.8% 
2.0% 
0.3% 
1.4% 
1.7% 
1.7% 
2.7% 
0.7% 
2.1% 
0.8% 
2.7% 
1.1% 
2.1% 
0.9% 
1.4% 

2026-‘30 
1.1% 
1.2% 
0.8% 
1.3% 
0.6% 
1.7% 
2.0% 
1.7% 
2.6% 
1.2% 
1.0% 
0.7% 
0.6% 
2.6% 
1.7% 
0.3% 
1.9% 
1.5% 
2.0% 
4.1% 
0.7% 
2.4% 
0.8% 
3.0% 
1.7% 
2.4% 
1.6% 
2.2% 

123  https://ec.europa.eu/energy/data-analysis/energy-modelling/eu-reference-scenario-2020_en 

79 

 
 
 
 
 
  
                                                 
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  

in $'15 per boe  2000 
38.4 
Oil 
26.5 
Gas (NCV) 

‘05 
65.4 
35.8 

in €'15 per boe  2000  2005 
58.9 
Oil 
31.7 
Gas (NCV) 

34.6 
23.4 

‘10 
86.7 
45.8 

‘10 
78.2 
40.6 

‘15 
52.3 
43.7 

‘15 
47.2 
38.7 

‘20 
39.8 
20.1 

‘20 
35.8 
17.8 

‘25 
59.9 
30.5 

‘25 
54.0 
27.0 

‘30 
80.1 
40.9 

‘30 
72.2 
36.2 

‘35 
90.4 
44.9 

‘35 
81.5 
39.7 

‘40 
97.4 
52.6 

‘40 
87.8 
46.6 

Source: Derived from JRC, POLES-JRC model, Global Energy and Climate Outlook (GECO) 

Technology assumptions 

‘50 

‘45 
105.6  117.9 
57.0 

57.8 

‘45 
95.2 
50.5 

‘50 
106.3 
51.2 

124  EUROPOP2019  population  projections:  https://ec.europa.eu/eurostat/web/population-demography-

migration-projections/population-projections-data  
2021  Ageing  Report :  Underlying 

125  The 

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. 

80 

 
 
 
 
 
                                                 
 
 
 
 
 
 
 
 
 
 
 
 
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. 

81 

 
 
 
 
                                                 
-  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. 

82 

 
 
 
 
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 

83 

0.0%0.5%1.0%1.5%2.0%2.5%3.0%TotalpassegertransportRoadRailIntra-EUaviationIWW andnationalmaritimeAnnual growth rates in Baseline'95-'15'15-'30'30-'500.0%0.5%1.0%1.5%2.0%2.5%3.0%Total freighttransportRoadRailIWW andnationalmaritimeAnnual growth rates in Baseline'95-'15'15-'30'30-'50 
 
 
 
 
 
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). 

84 

 
 
 
 
                                                 
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 
international  aviation  but  excluding 
international maritime, are projected to be 19% lower by 2030 compared to 2015, and 94% 
lower by 2050.  

including 

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. 

85 

0%10%20%30%40%50%60%70%80%90%100%BaselineBaseline201520302050% alternative fuels in transport methanolammoniae-gase-liquidsliquid biofuelnatural gasbiomethanehydrogenelectricity01002003004005006007008009001,000BaselineBaseline201520302050Mt of CO2inland waterways andnational maritimeaviationrailother road transportheavy goods vehiclesvanscars 
 
 
 
 
 
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 

86 

 
 
 
 
                                                 
-  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. 

87 

 
 
 
 
                                                 
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] 

88 

 
 
 
 
 
 
                                                 
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.  

89 

 
 
 
 
 
                                                 
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 

90 

 
 
 
 
 
                                                 
(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 

 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 

Impact on deployment 

  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 
GDPR/ePrivacy alignment and C-ITS Trust model 

deployment 

unblocked 

due 

to 

Improvement 
stakeholders are more involved in implementation. 

in  services  development  as 

ITS 

improvement 

PO1  +  Small 
in 
services  deployment  due  to  better 
data 
through  NAP 
coordination institutionalisation 

sharing 

Increased 
PO2  + 
of 
deployment 
services 
to 
SRTI and Day 1 C-
ITS 
services 
mandate 

due 

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 

Impact on deployment 

 Bundles 1 & 3 - increase 5 p.p. to 75% 

  Bundles 1 & 3 – 100% service 

 Bundles 1 & 3 - 

 Bundle 2 - same as Baseline 

 Bundle  4  &  5  –  enhanced  deployment  in  vehicles 

(see user uptake assumptions) 

conversion for TEN-T and 90% 
for other roads, 2 years after full 
coverage of data accessibility. 

same logic 
applied as in PO2 

 Bundle  2  -  same 

  Bundle 2 - same as Baseline 

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.  

91 

 
 
 
 
 
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 

 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 

Same as PO1 

Same as PO1 

No  direct  impact  on  user  uptake  - 
second  order  effect  as  a  result  of 
improved  services  availability  and 
effectiveness 

No direct impact on user uptake 
- second order effect as a result 
of 
services 
availability and effectiveness 

improved 

Impact on deployment 

  Bundles 1 & 3 – for cars, the user 
uptake  cap 
further 
+5p.p.  to  90%  in  2025.  For 
freight/PT, uptake fixed at 90% 

increases 

 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 
for 
5 
freight/buses) 

years 

and 

 Bundles  4  &  5  -  All  new  vehicles 
equipped in 2 full model vehicle cycles 

  Bundle 2 – Same as baseline 

  Bundles 4 & 5 - same as PO1 

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 

92 

 
 
 
 
 
 
 
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. 

93 

 
 
 
 
 
  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  services 144 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  https://www.euspa.europa.eu/system/files/reports/market_report_issue_6_v2.pdf 

94 

 
 
 
 
                                                 
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 

Upfront costs 

Ongoing costs 
(per year) 

Input 
€0 
€0 

Cost item 
Equipment 
App cost 
App development  €500,000 
Data  
App subscription 
Software updates 

€0 
€0 
20% capex 
(i.e. €100,000) 

Relevant bundles 
Cost owner 
Unit 
1A, 1B, 3 
End-user 
Per smartphone 
Per smartphone 
1A, 1B, 3 
End-user 
Per app platform  App developer  1A, 1B, 3 
1A, 1B, 3 
End-user 
Per smartphone 
Per smartphone 
1A, 1B, 3 
End-user 
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 

95 

 
 
 
 
 
                                                 
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/ 

96 

 
 
 
 
                                                 
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 

Upfront 
costs 

Ongoing 
costs 

Hardware, installation, 
integration, and licensing 
Software development 
Maintenance 

Secure Communications 
Data / app subscription 
Software updates 

Upfront costs 

€288 

Per vehicle 

Cost owner  Relevant 
bundles 
4, 5 

OEM 

€500,000 
5% of equipment 
costs 
€2.36 
€0 
€100,000 

Per model 
Per vehicle 

OEM 
End-user 

Per vehicle 
Per vehicle 
Per model 

End-user 
End-user 
OEM 

4, 5 
4, 5 

4, 5 
4, 5 
4, 5 

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 

97 

 
 
 
 
 
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 
Transmitter/receiver 
Antenna 
Electronic Control Unit 
Wiring 
On-board cellular equipment 
Installation 
Integration 
Total 

Value (€) 
160.0 
12.3 
55.4 
11.1 
12.3 
8.5 
28.5 
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  https://www.euspa.europa.eu/system/files/reports/market_report_issue_6_v2.pdf 

98 

 
 
 
 
 
                                                 
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: 

99 

 
 
 
 
  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  

Input 

Cost owner  Relevant bundles 

Unit 
Cost item 
Per RSU  Public body  5 
RSU equipment and installation  €14,116 
Per unit 
€68,104 
RSI equipment and installation 
Per unit 
€18,151 
RSI upgrade 
5% of CAPEX 
RSU Maintenance 
Per unit 
10% of CAPEX  Per unit 
RSI Maintenance 
Per unit 
€18.40 
Power consumption 
Per unit 
€100 
Data  
Per unit 
€37.91 
Secure Communications 

Public body  1A, 1B, 2, 3, 4, 5 
Public body  1A, 1B, 2, 3, 4, 5 
Public body  5 
Public body  1A, 1B, 2, 3, 4, 5 
Public body  1A, 1B, 2, 3, 4, 5 
Public body  1A, 1B, 2, 3, 4, 5 
Public body  1A, 1B, 2, 3, 4, 5 

Upfront costs 

Ongoing costs 

Upfront costs 

RSU equipment and installation 

100 

 
 
 
 
 
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 
Equipment/hardware 
Installation 
Total 

This is composed of: 

Value (€) 
6,617 
7,500 
14,117 

  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 

101 

 
 
 
 
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 

102 

 
 
 
 
                                                 
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 

NAP set up 

Input 

€273,500 

Unit 

Cost 
owner 
Per NAP  Public 

Relevant 
bundles 
1A, 1B, 2, 3, 4, 5 

Upfront costs 

TMC installation and integration 

€2,500,000  Per 

TMC 

body 
Public 
body 

1A, 1B, 2, 3, 4, 5 

103 

 
 
 
 
 
Cost item 

TMC upgrade 

NAP Maintenance 

Input 

Unit 

Cost 
owner 
Public 
body 

€175,000 

Per 
TMC 
€2,000,000  Per NAP  Public 

TMC Maintenance 

€250,000 

Data Collection - MMTIS 

€600,000 

body 
Public 
body 

Per 
TMC 
Per NAP  Public 

body 

Relevant 
bundles 
1A, 1B, 2, 3, 4, 5 

1A, 1B, 2, 3, 4, 5 

1A, 1B, 2, 3, 4, 5 

1A, 1B 

Ongoing 
costs 

Data Collection - RTTI 

€1,000,000  Per NAP  Public 

1B, 2 

body 

Data Collection - SRTI 

€300,000 

Per NAP  Public 

2, 3, 4, 5 

Data Collection – S&S Truck Parking 

€100,000 

Per NAP  Public 

3 

body 

Integration  of  transport  providers  on 
NAP 

€17,946 

Per NAP  Public 

1A 

body 

body 

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 

104 

 
 
 
 
 
 
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.  

105 

 
 
 
 
                                                 
  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 

106 

 
 
 
 
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 

107 

 
 
 
 
 
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 

108 

 
 
 
 
                                                 
  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. 
(MaaS) 

Bundle 1a - Multimodal travel information and booking/re-selling service 

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 

109 

 
 
 
 
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 

110 

 
 
 
 
                                                 
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

Service_and_changes_in_travel_preferences_and_travel_behaviour_a_literature_review 

https://www.researchgate.net/publication/330958677_Mobility-as-a-

111 

 
 
 
 
                                                 
 

 

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 

112 

 
 
 
 
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 

113 

 
 
 
 
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 

114 

 
 
 
 
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) 

115 

 
 
 
 
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. 

116 

 
 
 
 
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 

117 

 
 
 
 
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 

118 

 
 
 
 
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 

119 

 
 
 
 
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 

120 

 
 
 
 
                                                 
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 

121 

 
 
 
 
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 

122 

 
 
 
 
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 

123 

 
 
 
 
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. 
service 

Bundle  3  -  Road  safety-related  minimum  universal  traffic  information 

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  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.  

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 

124 

 
 
 
 
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).  

125 

 
 
 
 
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 

126 

 
 
 
 
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 

127 

 
 
 
 
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 

128 

 
 
 
 
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. 

160 Other impacts are not reduced in the same way, as these are not quantified in the support study produced 

for the GSR Regulation.  

129 

 
 
 
 
                                                 
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 

130 

 
 
 
 
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):  

131 

 
 
 
 
  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. 

132 

 
 
 
 
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 

133 

 
 
 
 
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. 

134 

 
 
 
 
  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. 

135 

 
 
 
 
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 

136 

 
 
 
 
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 

137 

 
 
 
 
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 

138 

 
 
 
 
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. 

139 

 
 
 
 
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 

140 

 
 
 
 
                                                 
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.  

141 

 
 
 
 
  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 

142 

 
 
 
 
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% 

penetration, 

76% 
safety impact estimate 

high 

EasyWay 

2.4% (average) 

2.8% (average) 

100% penetration 

3.3% (motorways) 

4.9% (motorways) 

EU-27, 2030 

EU-28, 2030 

2.8% 
roads) 

(interurban 

4.1% 
roads) 

(interurban 

1.6% (urban roads) 

2.0% (urban roads) 

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. 

143 

 
 
 
 
 
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? 

144 

 
 
 
 
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 

145 

 
 
 
 
 
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) 

3.1% (average) 

100% penetration 

5.2% (motorways) 

5.3% (motorways) 

EU-27, 2030 

146 

 
 
 
 
Study 

Fatalities 
(reduction) 

Injuries (reduction) 

Scenario 

(interurban 

5.3% 
and rural roads) 

5.3%  (interurban  and 
rural roads) 

1.7% (urban roads) 

1.9% (urban roads) 

eSafetyForum  2-10% 

CODIA 

4.2% 

2-10% 

3.1% 

NordicWay 

2.1% 

2.5% 

Not stated 

penetration, 
100% 
expected 
if  all 
vehicles  were  equipped, 
regardless of year 

impact 

31-65% 
penetration 
roads) 

traffic 

flow 
(all  main 

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. 

147 

 
 
 
 
 
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 

148 

 
 
 
 
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. 

149 

 
 
 
 
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) 

150 

 
 
 
 
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: 

151 

 
 
 
 
  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, 
safety 
impact estimate) 

high 

EU-28, 2030 

eIMPACT 

8.7% 

6.2% 

100% penetration 

EU-25, 2020 

152 

 
 
 
 
SAFESPOT 

7.1% 

4.9% 

100% penetration 

eSafetyForum 

2-10% 

CODIA 

7.2% 

2-10% 

4.8% 

EU-25, 2020 

Not stated 

penetration 

100% 
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. 

153 

 
 
 
 
 
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 

154 

 
 
 
 
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 

155 

 
 
 
 
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 

156 

 
 
 
 
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. 

157 

 
 
 
 
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. 

158 

 
 
 
 
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. 

159 

 
 
 
 
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 

160 

 
 
 
 
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% 

NordicWay 

3.5% 

3.9% 

76%  penetration,  high  safety 
impact estimate 

EU-28, 2030 

penetration  Finland, 

100% 
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) 

0.7% (V2I) 

100% penetration 

16.4% (V2V) 

8.6% (V2V) 

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 

161 

 
 
 
 
 
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. 

162 

 
 
 
 
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. 

163 

 
 
 
 
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 

164 

 
 
 
 
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 
High speed roads 
Rural roads 
Urban roads 

Low demand (billions) 
0 
358.7 
837.0 

High demand (billions) 
0 
153.7 
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 

165 

 
 
 
 
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 

166 

 
 
 
 
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. 

167 

 
 
 
 
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% 
GLOSA / TTG) 

(includes 

7.3% 
GLOSA / TTG) 

(includes 

SAFESPOT 

0.7%  (V2V  left-turn 
assist only) 

2.2%  (V2V  left-turn 
assist only) 

100% penetration 

EU-25, 2020 

100% penetration 

EU-25, 2020 

3.1%  (V2I  red  light 
violation, 
left  and 
right turn assistance) 

4.8%  (V2I  red  light 
violation, left and right 
turn assistance) 

CODIA 

3.7% 

6.9% 

penetration, 
100% 
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 

168 

 
 
 
 
 
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 

169 

 
 
 
 
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 

170 

 
 
 
 
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. 
(VRU) 

Bundle  6  -  Vulnerable  road  user  protection  –  pedestrians  and  cyclists 

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. 

171 

 
 
 
 
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 

172 

 
 
 
 
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 

173 

 
 
 
 
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.  

174 

 
 
 
 
  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 

Multimodal travel information service (including linking between modes) 

Multimodal travel information and booking/re-selling service (MaaS) 

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  

(Enhanced) Traffic network and incident management systems 

Mobility management services 

Road safety-related minimum universal traffic information service 

S&S truck parking location information system 

S&S truck parking location reservation system 

C-ITS safety-based V2V services: 

C-ITS V2I motorway focused applications: 

C-ITS V2I urban only applications:  

Table 58: Service overlaps in percentages 

Reference code 

1_MMTIS-1 

2_MaaS-1 

3_Tinfo-1 

4_RTTI-1 

5_Pinfo-1 

6_iFuel-1 

7_Tmang-2 

8_Mmang-2 

9_SRTI-3 

10_HDVPinfo-3 

11_HDVPres-3 

12_V2V-4 

13_V2Ihwy-5 

14_V2Iurb-5 

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 

0 

0 

0 

0 

0 

0 

0 

0 

100 

25 

100 

75 

50 

100 

25 

50 

100 

100 

100 

100 

100 

25 

25 

25 

25 

25 

100 

100 

100 

100 

100 

75 

75 

75 

75 

75 

50 

50 

50 

50 

50 

100 

100 

100 

100 

100 

100 

25 

100 

75 

50 

100 

100 

25 

100 

75 

50 

100 

25 

25 

25 

25 

0 

0 

0 

50 

50 

50 

50 

50 

50 

50 

0 

100 

25 

100 

75 

50 

100 

0 

50 

0 

100 

25 

100 

75 

50 

100 

25 

50 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

100 

75 

75 

75 

100 

100 

100 

100 

75 

75 

75 

100 

100 

100 

100 

75 

75 

75 

100 

75 

75 

75 

100 

100 

100 

100 

Impact 
Fuel 
consu
mption 
CO 

NOx 

VOC 

PM 
Fataliti
es 
Serious 
injuries 
Light 
injuries 
Materi
al 
damag
es 
Averag
e speed 

175