Contract No: imobility Challenge Report type: Deliverable 2.1. Version number: Version 1.0. Dissemination level:

Transcription

1 Contract No: imobility Challenge Report type: Deliverable 2.1 Report name: Mapping of the Systems Version number: Version 1.0 Dissemination level: Lead contractor: Public FIA Due date: January 2013 Date of preparation: imobility Challenge Partners: Fédération Internationale de l Automobile (FIA) Association des Constructeurs Européen d Automobiles (ACEA) Comité de Liaison de la Construction d Equipements et de Pièces Automobiles (CLEPA) European Road Transport Telematics Implementation (ERTICO) Teknologian Tutkimuskeskus (VTT) 1

2 Contributors Name Organization Notes Risto Öörni VTT Anna Schirokoff VTT Quality control Version Description Controller Date Comments 0.1 First version Mapping of systems completed 1.0 Full report completed Sara Rodriguez Authors (full list) Risto Öörni, Anna Schirokoff Project co-ordinator Gabriel Simcic Project Manager FIA Phone: +32 (0) Visiting address: Rue de la Science 41, 5 th Floor B-1040 Brussels 2

3 Contents Abbreviations 5 Executive summary 6 1. Introduction Background Objectives Terms and concepts 9 2. Method Overview Literature study Multicriteria analysis Selection of systems to be promoted Preconditions Systems to be promoted for decision-makers Systems to be promoted for consumers Candidate systems for promotion Overview Eco-driving assistance Eco-driving coaching ecall Fuel efficient route choice including advance planning Dynamic traffic light optimization and optimum speed advisory Cooperative adaptive cruise control Intersection safety assistant Start-stop assistant Tyre pressure monitoring system Cooperative local danger warning 33 3

4 4.12 Wrong way driving warning Traffic signal violation warning Speed alert Real-time traffic information Post crash warning Adaptive headlights Emergency braking Lane keeping support Blind spot monitoring Definitions of candidate systems Summary of results Discussion of results Conclusions Systems to be promoted Recommendations for further research References 56 4

5 Abbreviations Abbreviation Definition CACC Cooperative adaptive cruise control CEN European committee for standardization CO 2 Carbon dioxide DAB Digital audio broadcasting EC European commission FEA Fuel efficiency advisor FSD FSD Fahrzeugsystemdaten GmbH HC Hydrocarbons ITS Intelligent transport systems ICT Information and communication technologies ISA Intelligent speed adaptation ISO International organization for standardization NO X Nitrogen oxides OBD-II On-board diagnostics, version 2 RDS-TMC Radio data system traffic message channel RTTI Real-time travel and traffic information TC Technical committee TC278 Technical committee 278 TEN-T Trans-European transport network TPIS Tyre pressure indication system TPMS Tyre pressure monitoring system WG Working group 5

6 Executive summary The imobility Challenge project aims to demonstrate, promote and boost the deployment of ICT systems for energy efficient and sustainable mobility. The project also takes safety into account in all its activities because safety is an essential element of sustainability of transport and mobility and also reflected in the work carried out by imobility Forum. In addition to promotion of ICT systems for energy efficient and sustainable mobility, imobility Challenge carries out support studies to study the deployment status and impacts of the systems, to assess consumer awareness and demand and to obtain feedback from the users of the systems. The objective of the study was to provide a mapping of services and systems which support energy efficient and sustainable mobility. The main focus in the study was in cooperative ITS (intelligent transport systems) applications and systems which provide largest reductions in energy consumption and emissions. The aim of the study was to provide information on the deployment status of the systems, identify and list on-going research projects featuring the systems and provide information on potential impacts of the systems such as estimated CO2 reductions and safety impacts. This study will serve as background information for materials and deliverables to be produced later in the project, support the selection of systems to be promoted by imobility Challenge and act as background material for stakeholder discussions. The work was started by defining the most important terms and concepts and by clarifying the scope of the study. The study was then continued with a literature study to collect information on ICT systems for energy efficient and sustainable mobility, their impacts and deployment status. The systems identified in the literature study were then analysed using multicriteria analysis to identify the most potential systems which should be promoted to consumers and decision-makers. Before starting the multicriteria analysis, a criteria for systems to be promoted was established on the basis of the requirements collected from the project group and discussions with the stakeholder group involved in the project. When selecting systems to be promoted for decision-makers, the following minimum requirements were set: the system is available as a pilot or prototype to allow promotion and demonstration activities, the deployment horizon for the system is within five years, the system is relevant for at least one of the transport policy objectives, the system is either a cooperative system or a standalone in-vehicle system which contributes to a more sustainable and environmentally friendly transport system and that at least some information on impacts on environment is available. When selecting systems to be promoted for consumers, the following minimum requirements were identified: the system is available as a commercial product, the system is ready for deployment, the system is relevant for at least one of the transport policy objectives, the system is either a cooperative system or a stand-alone in-vehicle system which contributes to a more sustainable and environmentally friendly transport system and the system has impacts on environment documented in research. In total, 19 candidate systems were analysed in the study. 10 of them are covered by the list of priority imobility systems, and 10 of them are cooperative systems. Two systems (fuel-efficient route choice including advance planning and speed alert) have both cooperative and stand-alone implementations. 6

7 Nine of the 19 studied candidate systems were found to have at least potential positive impacts on environment. Of the nine systems having positive effects on environment, five systems (eco-driving assistance, eco-driving coaching, fuel-efficient route choice including advance planning, start-stop assistant and tire pressure monitoring system) had a quantitative estimate for reduction of CO2 or other emissions on the European level from earlier research. For the remaining four systems (speed alert, real-time travel and traffic information, cooperative adaptive cruise control, and dynamic traffic light optimisation and optimum speed advisory) the information on the impacts on CO2 emissions was specific to some conditions, covered only partly the functionality of the system or was a qualitative expert assessment. Of the cooperative systems having positive impacts on environment, only one (fuel-efficient route choice including advance planning) had a quantitative estimate for CO2 reduction on the European level. Most studies on the impacts on CO2 emissions are based on simulations, expert opinion or small-scale field tests; this was expected because of the novelty of the systems under analysis. 13 of the 19 candidate systems analysed in the study were found to have at least potential positive impacts on safety of road users. Of these 13 systems, seven were cooperative systems. The methods used to estimate safety impacts are rather heterogeneous due to differences between systems and their level of maturity. For most systems, the estimates for safety impacts are based on simulations, expert opinion and small-scale field tests. Only limited amount of research was found to be available on the impacts of cooperative systems on traffic fluency and service level provided by transport system. This partly related to the novelty of the systems. The following systems were selected for promotion to decision-makers on the basis of the results of multicriteria analysis: eco-driving coaching, speed alert (active gas pedal version, cooperative implementation standardised), dynamic traffic light synchronization and optimum speed advisory, cooperative adaptive cruise control, ecall, fuel efficient route choice (most advanced versions of fuelefficient route choice navigation would also use real time information so they have a cooperative element to it). The list contains three cooperative systems, two systems which exist as both cooperative and stand-alone systems and one stand-alone in-vehicle system. The following systems were selected for promotion to end-users on the basis of results of the multicriteria analysis: ecodriving assistance, real-time traffic information, start-stop assistant and tire pressure monitoring system. The list contains three stand-alone systems and one cooperative system. While implementation road maps were available for priority imobility systems, detailed deployment plans or implementation road maps were not available for most cooperative systems. Only few cooperative systems have deployment roadmaps which are publicly available and up to date. This means that expert opinion had to be used to determine the most likely deployment path and expected time of large-scale deployment for those systems. Deployment road maps should be drafted for systems which are seen the most promising in terms of impacts, cost-effectiveness and relevancy of impacts to policy goals. Most studies which have provided information on the impacts of cooperative systems have been carried out by the projects which have been developing the systems. However, independent evaluation of impacts is recommended to be carried out before large-scale deployment of the systems. Finally, establishing a repository for public deliverables of EC funded projects or encouraging the use of existing research document repositories should be considered to ensure the availability of research results related to cooperative systems. 7

8 1. Introduction 1.1 Background The imobility Challenge project aims to demonstrate, promote and boost the deployment of ICT systems for energy efficient and sustainable mobility. The project also takes safety into account in all its activities because safety is an essential element of sustainability of transport and mobility and also reflected in the work carried out by imobility Forum. imobility Challenge is the successor of esafety Challenge project launched by EC in While the main focus of the esafety Challenge project was in intelligent car systems and safety, the imobility Challenge project focuses on ICT systems facilitating energy efficient and sustainable mobility. In addition to promotion of ICT systems for energy efficient and sustainable mobility, imobility Challenge carries out support studies to study the deployment status and impacts of the systems, to assess consumer awareness and demand and to obtain feedback from the users of the systems. These support studies contribute to the objectives of the project by acting as support material and knowledge for dissemination, communication and campaigning. Related work has been carried out by imobility Implementation road maps working group and in esafety Support and icar Support projects ( These projects have provided implementation road maps for priority imobility systems identified by the imobility Forum (Kulmala and Öörni, 2012) and monitored the deployment of the imobility priority systems (Öörni and Mäurer, 2012). However, the imobility Implementation road map mainly focused on the existing imobility priority systems according to the priorities of the imobility Forum but did not provide an extensive mapping of potential new priority systems to be promoted. At present, systems aiming to reduce energy consumption of mobility and transport are covered by the ICT for Clean and Efficient Mobility working group of imobility Forum. The working group has started collecting information but it has not published its results yet (Anonymous, 2012). In other words, there is a need to carry out a mapping of potential ICT systems for energy efficient and sustainable mobility. At present, effects of ITS on sustainability of transport are an active research topic. For example, assessment methods for impacts of ITS on CO 2 emissions are being developed in the ECOSTAND project (ECOSTAND, 2012). 1.2 Objectives The objective of the study was to provide a mapping of services and systems which support energy efficient and sustainable mobility. The main focus in the study was in cooperative ITS (intelligent transport systems) applications and systems which provide largest reductions in energy consumption. The aim of the study was to provide information on the deployment status of the systems, identify and list on-going research projects featuring the systems and provide information on potential impacts of the systems such as estimated CO 2 reductions and safety impacts. 8

9 This study will serve as background information for materials and deliverables to be produced later in the project, support the selection of systems to be promoted by imobility Challenge and act as background material for stakeholder discussions. 1.3 Terms and concepts Sustainability Aspects of sustainability in transport sector have recently been addressed in Communication from the Commission - A sustainable future for transport: Towards an integrated, technology-led and user friendly system (European Commission, 2009). The trends and challenges identified include ageing of population, migration and increased mobility within EU, environmental challenges such as greenhouse gas emissions, noise and air quality, increasing scarcity of fossil fuels, and urbanisation which contributes to increased congestion. At present, there are several definitions for sustainable transport (Jeon and Amekudzi, 2005). While there is no single definition available for sustainable ITS, the political objectives related to sustainability included in European Transport Policy have been described as: to establish a sustainable transport system that meets society s economic, social and environmental needs and is conducive to an inclusive society and a fully integrated and competitive Europe (European Commission, 2009). In the context of this work, sustainability is understood as a combination of economic, social and political objectives. The main emphasis of the work is in applications which contribute to sustainable transport by reducing adverse effects on environment such as emissions and noise and reducing consumption of non-renewable natural resources such as fossil fuels. Cooperative system Although there have been several research projects on cooperative ITS, such as DRIVE C2X and CVIS, there is a need to provide a clear definition. CEN TC278 WG 16 and ETSI TC ITS have defined cooperative ITS in the following way: A co-operative ITS is a subset of the overall ITS that communicates and shares information between ITS Stations to give advice or facilitate actions with the objective of improving safety, sustainability, efficiency and comfort beyond the scope of stand-alone systems. (Schade, 2010.) 9

10 2. Method 2.1 Overview The work was started by defining the most important terms and concepts and by clarifying the scope of the study. The study was then continued with a literature study to collect information on ICT systems for energy efficient and sustainable mobility, their impacts and deployment status. The systems identified in the literature study were then analysed using multicriteria analysis to identify the most potential systems which should be promoted to consumers and decision-makers. Before starting the multicriteria analysis, a criteria for systems to be promoted was established on the basis of the requirements collected from the project group and discussions with the stakeholder group involved in the project (Chapter 3). 2.2 Literature study An extensive literature study was carried out. The most appropriate databases and search engines such as Engineering Village, Scopus and Transport (Ovid), TRB TRID database, TRB Research in Progress (RIP) database and Google were used when searching relevant studies and information. Also, the latest proceedings of the ITS World and ITS Europe congresses were studied. ERTICO provided a list of relevant on-going projects. 2.3 Multicriteria analysis The main objective of the multicriteria analysis carried out as a part of the mapping of systems was to identify the applications which are ready to be promoted in terms of technological maturity and commercial availability, contribute to the stated policy objectives and correspond to the scope and priorities of the project. The analysis was started by defining a framework to be used in analysis which was then used to supplement the plan for literature study and reporting of study results. The criteria to be used in the multicriteria analysis was essentially based on criteria for systems to be promoted to consumers and decision-makers described in Chapter 3. The different elements of the criteria used in the analysis were divided into two groups: background information related to the system and the main part of the criteria. The background part indicates whether the system is already in the list of priority systems identified by imobility Forum or whether the system is a cooperative system. The main part of the criteria covers the impacts of the system, technological maturity, expected time horizon for deployment and possible other implementation issues. The impacts of the systems were evaluated using three different levels. The criteria used for evaluating the impacts of the systems, was defined on the basis of the quantity and quality of the research available and the magnitude of the impact indicated in research results. One mark was given - to applications for which only limited impacts to the stated policy objective were indicated in research results - in cases where potential for achieving the impacts was identified but there was some uncertainty whether the impacts will be actually realised - in cases where the evidence available on the existence and magnitude of the impact was limited. 10

11 Two marks were given in cases - where the impacts indicated in research results were substantial - the results are based on at least two studies independent of each other - there is a reasonable confidence that the impacts will be realised in a real traffic environment. Three marks were given in cases - where studies on the impacts are based one or more field test carried out in realistic operating conditions - the impacts have been found to be substantial and preferably larger than in cases where two marks are given. Technological maturity of the system was also evaluated using a classification with three steps. Three marks were given to systems which are available as commercial products. Two marks were given to systems which exist in the form of a prototype or pilot and are planned for commercial launch within five years. One mark was given to systems which exist as prototypes or pilots with no known or expected date for commercial availability. Time horizon for deployment was also evaluated using three different levels. Three marks were given to systems which are ready for deployment immediately. Systems which received two marks were considered ready for deployment within the next five years. One mark was given to systems which were considered to be ready for deployment after more than five years. 11

12 3. Selection of systems to be promoted 3.1 Preconditions One of the aims of the mapping of systems was to identify systems which should be promoted to consumers and decision-makers later in the project. Therefore, a criterion was needed to select the systems to be promoted in the project. Information from earlier studies, such as imobility Implementation road map, and extensive discussions with project partners and stakeholder group of the project were used as sources of information when defining the criteria. First, the mapping of applications has to take into account the impacts of the systems and the relevancy of the impacts to policy objectives. In this study, policy objectives to be addressed were defined to be the goals expressed in the ITS directive (European Commission, 2010) and the objectives adopted by the imobility Forum. Systems to be selected for promotion must have impacts relevant to the policy goals and there has to be at least some evidence based of the impacts of the system available from earlier research. Second, the systems to be promoted have to be technologically mature enough. Availability of tested and piloted solutions may be a significant barrier or enabler for the deployment of a system. There is usually little point in promoting to consumers a system which is not available as a commercial product or promoting to decision-makers a system which exists only as an idea or concept. Third, the expected time horizon for large scale deployment of the system is important parameter when preparing a plan how to promote the system to consumers and decision-makers or to facilitate its deployment by other means. The promotion and dissemination activities to be carried out in imobility Challenge will focus on systems which are ready for large-scale deployment in near future. In other words, systems which were not considered ready for large-scale deployment within five years were considered unsuitable to be promoted in imobility Challenge. Time horizon for deployment was assessed for each system on the basis of technological maturity, commercial availability and other factors related to the system such as socio-economic benefits and costs of the system and system-specific barriers and enablers for deployment. Time horizon for a deployment of system is usually dependent on numerous different factors such as technological maturity, trends in cost of implementation, expected developments in regulation related to the system, status of ICT infrastructure required to implement the service and availability and completeness of standards related to the system. Assessment of time horizon for deployment or readiness for deployment involves certain assumptions which are related to the future of the system under analysis. Uncertainties may be related, for example, to business decisions of key stakeholders, price development of components needed to realise the system, development of regulation and user acceptance. The assessment of time horizon for deployment has to be based on expert opinion if no detailed deployment plan or deployment roadmap is available for the system under analysis. Technological maturity of the system is closely linked to the time horizon of deployment: availability of the system as a commercial product is an important prerequisite for large-scale deployment of the system. Availability of the system as a functional pilot or prototype also has implications for the 12

13 deployment of the system. Systems which exist at least as pilots or prototypes can be evaluated in terms of functionality, technical performance and impacts, and this information is typically required before large-scale deployment can take place. 3.2 Systems to be promoted for decision-makers When selecting systems to be promoted for decision-makers, the following minimum requirements were set: - The system is available as a pilot or prototype to allow promotion and demonstration activities. - The deployment horizon for the system is within five years. - The system is relevant for at least one of the transport policy objectives. - The system is either a cooperative system or a stand-alone in-vehicle system which contributes to a more sustainable and environmentally friendly transport system. - At least some information on impacts on environment is available. 3.3 Systems to be promoted for consumers When selecting systems to be promoted for consumers, the following minimum requirements were identified: - The system is available as a commercial product. - The system is ready for deployment. - The system is relevant for at least one of the transport policy objectives. - The system is either a cooperative system or a stand-alone in-vehicle system which contributes to a more sustainable and environmentally friendly transport system. - The system has impacts on environment documented in research. 13

14 4. Candidate systems for promotion 4.1 Overview imobility Implementation Road Map imobility implementation road map provides implementation road maps for priority imobility systems identified by the imobility Implementation road maps working group (Öörni and Kulmala, 2012). The report provides definitions for the priority systems, summarizes their safety, traffic efficiency and environmental impacts, and provides implementation road maps for them. Information provided on the impacts of the systems is already available in the imobility effects database (icarsupport, 2012). The safety, traffic efficiency and environmental impacts described in the imobility Implementation road map are presented in Tables 1 2. Table 1: Expected safety impacts of imobility priority systems based on research results and expert assessments (Kulmala and Öörni, 2012). System Accident type specifically affected Local results in specific conditions for effects on all accidents for vehicles or roads equipped based on research incorporating accident analysis Obstacle & collision rear-end crashes - warning Emergency braking rear-end crashes all fatalities EU -7% all injuries EU -7% Blind spot monitoring side collisions - Lane keeping support RTTI Dynamic traffic mgmt (VMS) Local danger warning Extended environmental information head-on or run-off-road, side collisions accidents in adverse conditions, pile-ups accidents in adverse conditions, pile-ups accidents in adverse conditions, pile-ups accidents in adverse environmental conditions injuries EU -2 to -6% all fatalities EU -5 to -10% accidents in slippery conditions -5 to -15% all injury crashes -5 to -20% all fatal crashes -10 to -25% all injury crashes -1 to -15% ecall all fatalities -2 to -15%; EU -6% severe injuries -3 to -15%; EU -6% Speed alert (active accelerator pedal version) Dynamic navigation Eco-driving accidents caused by exceeding speed limits all accidents accidents caused by exceeding speed limits - all injuries EU -6% all fatalities EU -9% reduced exposure but increased accident rate due to driving on lower category roads Similar effects as speed alert if the functionality includes that part 14

15 System Table 2: Expected efficiency and environmental benefits of imobility priority systems based on research results and expert assessments (Kulmala and Öörni, 2012). Efficiency impacts (effects on travel time and total delays) Environmental impacts (effects on fuel consumption and CO 2 emissions) Obstacle & collision motorways: % -3% warning Emergency braking reduction in congestion costs: 0.27% % ~0% Blind spot monitoring - - Adaptive head lights - - Lane keeping support reduction in congestion costs: ~0% % RTTI - may increase or decrease Dynamic traffic mgmt (VMS) Local danger warning Extended environmental information ecall Speed alert (active accelerator pedal version) Dynamic navigation ramp metering: % ** hard shoulder running: -2%.. -26% ** variable speed limits: -5% % -1%.. -2% (impact on average speed: -1%.. -2%) ** ramp metering: -2.5% % ** hard shoulder running: -4% ** variable speed limits: may increase or decrease very small - - reduction in congestion costs: <0.1% ~0% urban roads: -1.1% % may increase or decrease rural roads: -0.5% % (impact on average speed: urban roads: % rural roads %) - -2% Eco-driving - -3%.. -11% ** estimate applicable to certain location or conditions Impact of Information and Communication Technologies on Energy Efficiency in Road Transport Potential impacts of various vehicle-based ITS systems on CO 2 emissions were estimated in a study carried for EC in 2009 (Klunder et al., 2009). Estimates for potential CO 2 effect at European level, ease of implementation, presence of compliance issues and expectations for future deployment are described in Table 3. Of the systems presented in Table 3, only those which were considered to be within the scope of imobility Challenge were considered in further analyses. For example, usage based insurance (PAYD, pay as you drive) was not included because insurance products typically are complex products based on a contract between the customer and the insurance company and they would therefore be less suitable for promotion by any third party like the imobility Challenge project. For example, the terms and conditions of the service as well as the service offerings may be very different between service providers and EU member states. 15

16 CO 2 reduction Table 3: Overview of potential CO 2 effects, ease of implementation, compliance and expected future use for promising measures (Klunder et al., 2009). System Potential CO 2 effect EU27 Ease of implementation Compliance issue Expected future use Eco-driver Coaching 15% Medium Medium Large Eco-driver Assistance 10% Easy Medium/Hard Large PAYD 7% Medium Medium Medium Platooning 6% Very hard Hard Small CC/ACC 3% Easy Easy Large Fuel-efficient route choice 2% Medium/hard Medium Medium Dynamic traffic light synchronization 2% Medium No issue Large Automatic engine shutdown 2% Easy Easy Large Trip-departure planning (freight) 2% Medium Medium Large Tyre pressure indicator 1% Easy Medium Large Congestion charging 0.5% Medium No issue Medium Slot Management 0.05% Hard No issue Small Lane Keeping 0.008% Easy Easy Large Emergency Braking 0.007% Easy No issue Large Mapping of systems in terms of the potential CO 2 reduction and ease of implementation is illustrated in Figure 1. The potential CO 2 reduction is based on the maximum possible use of the system, i.e. a 100% penetration rate of an in-vehicle system, or application on all suitable roads and areas. This reduction is given as a percentage of the total CO 2 emission by road transport in the EU % 14% Eco-driver Coaching 12% 10% Eco-driver Assistent 8% 6% PAYD Platooning 0 4% 2% 0% CC/A CC Dyn. traffic Fuel-eff. Trip- light synchr Aut. eng. Route- shutdown departure choice planning Tyre pressure Congestion ind. charging Easy Ease of implementation Very hard Figure 1: Overview of potential CO 2 effects versus the ease of implementation (Klunder et al., 2009). 16

17 eimpact The safety and traffic impacts of intelligent vehicle safety systems were studied in the eimpact project in 2008 (Wilmink et al., 2008). The systems analysed in eimpact were partly the same as in imobility implementation roadmap. The systems analysed in eimpact are listed in Table 4. System name Electronic Stability Control Full Speed Range ACC Emergency Braking Pre-Crash Protection of Vulnerable Road Users Lane Change Assistant (Warning) Table 4: Systems analysed in eimpact and their descriptions. Description Stabilises the vehicle within the physical limits and prevents skidding through active brake intervention and engine torque control. Adaptation of speed and distance to vehicles ahead down to standstill, including Stop and Go. Fully automatic system, avoids or mitigates longitudinal crashes (braking only). Detection of vulnerable road users and fully automatic emergency braking (no passive safety). Warning for nearby vehicles next to or at the rear of the vehicle just before lane change. Lane Keeping Support Lane keeping assistance by active steering support (Phase 2) Night Vision Warning Enhanced vision at night through near or far infrared sensors, including obstacle warning. Driver Drowsiness Monitoring and Warning ecall (one-way communication) Intersection Safety Wireless Local Danger Warning Speed Alert Warns drivers when they are getting drowsy. Automatic emergency call for help in case of an accident. Red light warning, right of way information at signalized intersection and stop signs and left turn assistance. Inter-vehicle communication distributing early warnings for accidents, obstacles, reduced friction and bad visibility. Map and camera based system warning for speed limits by use of a haptic gas pedal and warning module for when speed limit is exceeded. The eimpact project assessed the safety impacts of the systems in scenarios with expected high and low fleet penetrations in EU25 in years 2010 and 2020 and in a scenario with 100% fleet penetration. Estimates for safety impacts provided by the eimpact project are summarised in Table 5. 17

18 Table 5: Safety impacts of systems analysed in eimpact, 100% fleet penetration assumed (Wilmink et al., 2008). System name Safety effect on fatalities by system in full penetration rate Safety effect on injuries by system in full penetration rate Electronic Stability Control -16.6% -6.6% Full Speed Range ACC -1.4% -3.9% Emergency Braking -7.0% -7.3% Pre-Crash Protection of Vulnerable Road Users -1.8% -1.9% Lane Change Assistant (Warning) -2.2% -4.8% Lane Keeping Support -15.2% -8.9% Night Vision Warning -2.9% -2.0% Driver Drowsiness Monitoring and Warning -5.0% -3.6% ecall (one-way communication) -5.8% +0.1% Intersection Safety -3.9% -7.3% Wireless Local Danger Warning -4.5% -2.8% SpeedAlert (fixed speed limits only) -6.8% -4.5% SpeedAlert (dynamic, including variable speed limits) -8.7% -6.2% The avoided congestion costs for the systems analysed in eimpact in Europe in high and low penetration scenarios in 2010 and 2020 are summarised in Table 6. Table 6: Impacts on congestion costs in Europe in scenarios with low and high fleet penetration in 2010 and 2020 (Wilmink et al., 2008). System name Avoided congestion costs (M EUR) 2010 (low-high) 2020 (low-high) Electronic Stability Control Full Speed Range ACC Emergency Braking Pre-Crash Protection of Vulnerable Road Users Lane Change Assistant (Warning) Lane Keeping Support Night Vision Warning Driver Drowsiness Monitoring and Warning ecall (one-way communication) Intersection Safety Wireless Local Danger Warning SpeedAlert CODIA EU project CODIA (Co-Operative Systems Deployment Impact Assessment) aimed to provide an independent assessment of direct and indirect impacts, costs and benefits of the following cooperative systems (Kulmala et al., 2008): - Speed adaptation due to weather conditions, obstacles or congestion (V2I and I2V communication) - Reversible lanes due to traffic flow (V2I and I2V) - Local danger / hazard warning (V2V) - Post-crash warning (V2V) - Cooperative intersection collision warning (V2V and V2I). 18

19 The estimated safety effects of these systems are presented in Table 7 and other impacts of four systems in Table 8. Table 7: Safety effects of systems analysed in CODIA with 100% penetration and the expected low and high penetration values (%) in 2020 and 2030 (Kulmala et al., 2008). Fatalities System 100 % 2020 low 2020 high 2030 low 2030 high Dynamic speed adaptation -7.2 % -0.3 % -1.0 % -3.2 % -4.2 % Reversible lanes 0.0 % 0.0 % 0.0 % 0.0 % 0.0 % Local danger warning -4.2 % -0.2 % -1.0 % -2.1 % -3.9 % Post crash warning -1.4 % -0.2 % -0.8 % -0.7 % -1.1 % Cooperative intersection collision warning -3.7 % 0.0 % 0.0 % 0.0 % -0.2 % Injuries System 100 % 2020 low 2020 high 2030 low 2030 high Dynamic speed adaptation -4.8 % -0.2 % -0.7 % -2.1 % -2.5 % Reversible lanes 0.0 % 0.0 % 0.0 % 0.0 % 0.0 % Local danger warning -3.1 % -0.1 % -0.8 % -1.6 % -2.9 % Post crash warning -0.7 % -0.1 % -0.5 % -0.3 % -0.6 % Cooperative intersection collision warning -6.9 % 0.0 % 0.0 % -0.1 % -0.4 % Table 8: Impacts of four cooperative systems studied in CODIA described by different criteria. (+++ means very positive, ++ positive, + slightly positive, 0 negligible effect, - slightly negative, -- negative, --- very negative) (Kulmala et al., 2008). Criteria I2V Dynamic speed adaptation I2V Reversible lane control V2V Local danger warning V2V Post-crash warning Benefit/Cost Safety Efficiency Emissions Noise Mobility Comfort EU competitiveness ITS industry Postponing investments Eco-driving assistance Description imobility Implementation road map (Kulmala and Öörni, 2012) provides a definition for Eco-driving assistance: Eco-driving assistance assists and encourages the driver to eco-driving by providing information to the driver about the current fuel consumption, energy use efficiency and appropriate gear selection taking into account engine and transmission efficiency, vehicle speed and rate of acceleration etc. Apart from displaying instantaneous and mean fuel consumption on the instrument panel (from the on-board computer), there can be an Eco-Drive Indicator, which indicates when the vehicle is being operated in a fuel-efficient manner with respect to driveline efficiency. The measure also informs the driver when a gear shift is appropriate. 19

20 This definition covers, for example, vehicles with an eco-driving indicator, gear change indicator or other systems providing guidance to the driver how to operate the vehicle in a most environmentally efficient way. Eco-driving assistance may also include speed alert functionality which informs the driver when he or she exceeds the legal speed limit. Impacts A literature study in the safety, traffic efficiency and environmental impacts of eco-driving has been carried out by the icarsupport project. According to the imobility Implementation road map (Öörni and Mäurer, 2012) and imobility effects database (icarsupport, 2012), eco-driving has potential to reduce CO 2 emissions and fuel consumption by 3 11%. The impact estimate provided in the imobility Implementation road map has been given for eco-driving including both eco-driving assistance and eco-driving coaching. In practise, eco-driving coaching is only available in the form of pilots and prototypes, studies available on the impacts of eco-driving coaching are very few and imobility Forum has its focus in a limited number of systems close to large-scale deployment. Therefore, this estimate reflects the impacts of eco-driving assistance instead of eco-driving coaching. The estimate is also in line with results provided in (Klunder et al., 2009). Systems which include speed alert functionality have safety effect corresponding to other speed alert systems. Evidence on the impacts of eco-driving assistance applications on traffic efficiency or other than CO 2 is limited and inconclusive at present (Kulmala and Öörni, 2012). Effects of The Fuel Efficiency Advisor (FEA) were studied in EuroFOT project. It is a system that provides in real time the current location of the vehicle, its fuel consumption, messages, driver times, service intervals and much more to support fuel-efficient driving, or eco-driving. The system consists of on-board functions for the driver as well as follow-up reports in the back-office system. The field test showed a reduction in fuel consumption of 1.89% but the effect was not statistically significant. (Faber et al., 2012) The impacts of eco-driving assistance and eco-driving coaching will depend on driver compliance to the recommendations given by the in-vehicle system. Simulator studies have showed that drivers will be less able to use eco-driving style when the traffic environment is highly demanding such as in residential areas and during critical situations. Time pressure was also found to reduce the performance in fuel saving goal for the group which had to manage both time saving and fuel saving goals. (Dogan et al., 2011) Deployment status and time horizon for large-scale deployment The deployment status of eco-driving has been analysed in the imobility Implementation road maps monitoring report on the basis of data compiled by FSD in Germany and a literature study. About 1 5% of new registered passenger cars in EU27 in 2010 were estimated to have at least some ecodriving features in the vehicle (Öörni and Mäurer, 2012). Because no vehicles equipped with ecodriving coaching are known to be on the market, the figures mentioned above apply to eco-driving assistance. Implementation of Eco-driving assistance is easy. Forecasted use is expected to increase, since implementation is straightforward and there is, and will be, much focus on fuel consumption. There 20

21 are no main barriers or risks associated with the measure. No significant barriers for large-scale deployment within five years are expected. The results of a recent questionnaire indicate that systems providing eco-driving assistance and support before, during or after the trip are generally rated positively by drivers but their willingness to pay for the systems is very limited (Trommer and Höltl, 2012). Research projects The FREILOT service (FREILOT consortium, 2012) provides direct support for an economic driving style. The eco-driving function supports the driver to optimise the vehicle s fuel economy through his/her acceleration, braking and gear-changing behaviour. While driving, continuous information on accelerator position, instant consumption, average consumption and a general performance rating on eco-driving level is provided to the driver. If one of the parameters has very low performance the driver receives a message requesting him to improve his behaviour in terms of fuel consumption. The objective of the ECOSTAND project (ECOSTAND, 2012) is to provide support for an agreement between European Union, Japan and United States on a framework for a common assessment methodology for determining the impacts of ITS on energy efficiency and CO 2 emissions. This support will involve the formulation of policy advice, a joint research agenda to identify research gaps and to propose solutions to enable the methodology to be developed. ECOSTAND has started its work 2012 and provided an inception report but not further results yet. 4.3 Eco-driving coaching Description Definition of eco-driving coaching is provided together with eco-driving assistance in the imobility Implementation road map (Kulmala and Öörni, 2012): Eco-driving assistance assists and encourages the driver to eco-driving by providing information to the driver about the current fuel consumption, energy use efficiency and appropriate gear selection taking into account engine and transmission efficiency, vehicle speed and rate of acceleration etc. Apart from displaying instantaneous and mean fuel consumption on the instrument panel (from the on-board computer), there can be an Eco Drive Indicator, which indicates when the vehicle is being operated in a fuel-efficient manner with respect to driveline efficiency. The measure also informs the driver when a gear shift is appropriate. Eco-driving coaching utilises preview information to enable optimal advance planning. The preview information, obtained from enhanced map data, should include road slope and curvature and road attributes such as speed limits, stop signs etc. Compared with Eco-driving Assistance, the system tends to have at least some of the following features: recommendation of optimal speed profiles, especially regarding deceleration and avoidance of unnecessary stops etc. Eco-driving coaching includes at least some features of eco-driving assistance but differs from ecodriving assistance in the utilisation of preview information. 21

22 Impacts Eco-driving coaching has been estimated to reduce CO 2 emissions from road traffic in Europe by 10 20% (Klunder et al., 2009). This is consistent with the estimates provided for eco-driving assistance. The safety and traffic efficiency impacts of eco-driving coaching can be expected to be comparable to eco-driving assistance because the features are partly the same but implemented in a different way. Deployment status and time horizon for large-scale deployment At present, eco-driving coaching has not been deployed, and the system exists only as a concept or as early prototypes. Short overview on the subject has been provided in the introduction of (Kamal et al., 2011). However, the implementation of the system would be relatively easy and enhanced map data will become available for a larger share of roads in future (Klunder et al., 2009). The cost of the measure is from relatively low to medium (Klunder et al., 2009). Coverage of enhanced map data required by eco-driving coaching has been estimated to be 5 10% of the main roads in such as the TEN-T network in Europe (Öörni and Mäurer, 2012). This estimate is based on a literature study and expert assessment. Elements of eco-driving coaching such as digital map providing preview information are included in the system under development in the ECOMOVE project (Eikelenberg, 2010). A prototype system providing dynamic eco-driving messages based on the status of traffic flow on interurban road have also been evaluated and tested in the US (Barth and Boriboonsomsin, 2009). The results of a recent questionnaire indicate that systems providing eco-driving assistance and support before, during or after the trip are generally rated positively by drivers but their willingness to pay for the systems is very limited (Trommer and Höltl, 2012). The main obstacle to the deployment of the system is the availability of preview information such as enhanced map data. On the other hand, the cost of the system is relatively limited and its implementation is relatively easy. Any large-scale deployment of the system requires sufficient coverage of preview information such as enhanced map data. The system will most likely be deployed as an additional functionality to existing eco-driving systems providing recommendations and other information to the driver. Therefore, a gradual deployment with increasing coverage of map data is seen possible, and the system can be considered ready for large-scale deployment within five years. Research projects Features related to eco-driving coaching such as a digital map providing preview information are a part of the ECOMOVE project (Eikelenberg, 2010). 4.4 ecall Description ecall is the European in-vehicle emergency call system. When sensors installed in the vehicle detect an accident or the vehicle occupants activate ecall manually, the ecall in-vehicle system opens a call to emergency number 112, sends the minimum set of data (MSD) to public safety answering point (PSAP) using an in-band modem, and opens a voice connection between PSAP and vehicle occupants. 22

23 The minimum set of data sent to PSAP includes the location of the accident, details of the vehicle and other relevant information. The core standards of pan-european ecall are EN15722, EN16052 and EN16062 as well as ETSI/3GPP standards defining the ecall in-band modem. A short written definition for ecall is provided in EN16062 (ecall High Level Application Requirements): Emergency call generated either automatically via activation of in-vehicle sensors or manually by the vehicle occupants; when activated it provides notification and relevant location information to the most appropriate Public Safety Answering Point, by means of mobile wireless communications networks, carries a defined standardised minimum set of data (MSD) notifying that there has been an incident that requires response from the emergency services, and establishes an audio channel between the occupants of the vehicle and the most appropriate Public Safety Answering Point. Impacts According to the eimpact study (Wilmink et al., 2008), ecall will most probably, if installed in all vehicles, reduce the number of road accident fatalities in Europe by 5.8%, but slightly, by 0.1%, increase injuries because most of the prevented fatalities are expected to turn into injuries. The traffic impacts of ecall were also estimated in eimpact (Wilmink et al., 2008). While ecall was not assumed to have any direct impacts on fluency of traffic or travel times, it was estimated to have a small positive indirect effect on congestion costs in consequence of the faster response to the accidents (5 7 million euro in a year in Europe) (Wilmink et al., 2008). Savings in congestion costs because of ecall have been estimated to be <0.1% in EU25 (Kulmala and Öörni, 2012). The effects of ecall on CO 2 emissions are mainly related to reduction of congestion because of faster accident clearance. The effect of ecall on CO 2 emissions on European level (0.008%) has been assumed to be of the same magnitude with the corresponding effect of lane keeping support (Wilmink et al., 2008; Kulmala and Öörni, 2012). Deployment status and time horizon for large-scale deployment The standards of pan-european ecall have been completed recently. The standards and specifications are now being validated in the HeERO project (Harmonized ecall European Pilot) (HeERO, 2012). In other words, pilots of pan-european ecall have been set up in several member states but ecall is not available as a functional service or a commercial product. After a public consultation and assessment of policy options, European Commission has decided to take the regulatory approach to the deployment of ecall. The current aim of the EU is to have ecall implemented in all vehicles type-approved in the EU in 2015 or later, and to have all PSAPs compatible with ecall in the EU Member States by 2015 (European Parliament, 2012). Research projects HeERO project (Harmonized ecall European Pilot) (HeERO, 2012) prepares the deployment of ICT infrastructure necessary for ecall. HeERO involves 10 member states and associated states. HeERO2 project started in 2012, and it continues the work carried out in HeERO in member states not participating in the HeERO project. 23

24 The utilization of the information included in the ecall minimum set of data (MSD) by the traffic management centre has been studied in the FOTSIS project (FOTsis, 2013a). High-level description from driver point of view A high-level illustration has been provided by Euro NCAP (Figure 2). Figure 2: ecall (Euro NCAP 2013). 4.5 Fuel efficient route choice including advance planning Description A definition of fuel efficient route choice including advance planning is provided by Klunder et al. (2009): Fuel-efficient Route Choice is a nomadic device navigation system where optimisation of route choice is based on the lowest total fuel consumption instead of the traditional shortest time or distance. The system is expected to take into account static information like trip length and speed limits. Also road gradients and curvatures can be taken into account, if such information is available. The most advanced version of fuel-efficient route choice navigation would take into account dynamic real-time information about congestion and traffic incidents from probe vehicles running in the street network. This measure could be implemented together with Map enhanced eco-driving measures ( eco-driver Coaching ), since both require map data, however, dynamic fuel efficient route choice also requires information about traffic flow. The more advanced version of the system which utilizes real-time traffic information for route calculation requires communication between in-vehicle system and back-office systems. Therefore, it clearly has a cooperative element. A definition is proposed for the system on the basis of description presented in ICT4EE study (Klunder et al., 2009): Fuel efficient route choice is a navigation system where optimisation of route choice is based on lowest total fuel or energy consumption instead of the traditional shortest time or distance travelled. The system is expected to take into account static information like trip length and speed limits. Also road gradients and curvatures can be taken into account, if such information is available. The most 24

25 advanced version of fuel-efficient route choice would take into account dynamic real-time information about congestion and traffic incidents from probe vehicles or other sources. Impacts The impacts of the system on CO 2 emissions in Europe have been estimated by Klunder et al. (2009). Reduction in CO 2 emissions due to improved route choice were estimated to be proportional to the amount of fuel used. Reduction of emissions because of improved route choice on the basis of static information such has trip length or speed limit were calculated on the basis by assuming that 26% of vehicle kilometres are driven on urban roads and that the effect in urban areas is a 4 % reduction in emissions and that the corresponding impact on motorways and rural roads is 1%. These figures were obtained from Ericsson et al. (2006). The authors concluded that total reduction in CO 2 emissions due to improved route choice based on static information would most likely be 1.7% in Europe. Level of driver compliance to the instructions was not taken into account when calculating the estimate. Klunder et al. (2009) also estimated how much real-time information on congestion improves route choice of the driver and how large additional reduction in CO 2 emissions can be expected in Europe. The share of congested kilometres of all vehicle kilometres was assumed to be the same as in the eimpact project (Wilmink et al., 2008), and effect of congestion information on emissions was assumed to be 20% for all road types. The total reduction in emissions due to real-time congestion information and improved route choice was estimated to be 0.4% in Europe. The combined impact of route planning on the basis of static information and congestion information was estimated to be 2.1% in Europe. The impacts of the service are dependent on driver motivation and compliance with the instructions provided by the service. In addition to reducing emissions and fuel consumption, the driver may have other goals such as time constraints (Dogan et al., 2012). Deployment status and time horizon for large-scale deployment At least one prototype of fuel efficient route choice including advance planning is known to be under development in Europe. Subproject SP4 of the ECOMOVE project is developing a Truck econavigation application which calculates the most fuel efficient route based on truck specific attributes, traffic patterns, eco-maps and real-time traffic information (ECOMOVE consortium, 2012). At the same time, SP3 of ECOMOVE (ecosmart Driving) is developing eco-driving applications such as eco-pre-trip Planning, ecosmart Driving (including dynamic green routing, eco-driving assist and eco-information) and ecoposttrip. GreenGPS project of the University of Illinois is developing a service which calculates the most fuel-efficient route between origin and destination using a digital map and sensor data obtained from the vehicle via OBD-II interface (University of Illinois, 2013). One of the potential barriers for deployment is the users willingness to pay for eco-driving features (Trommer and Höltl, 2012). The availability of enhanced map data such as speed limits and other attributes of the road network is also limited at present. For example, coverage of available speed limit data has been estimated to be 5 20% of the TEN-T road network (Öörni and Mäurer, 2012). Efforts to make speed limit data available to developers are currently being coordinated by ROSATTE Implementation Platform (Hovland, 2012). 25

26 Large-scale deployment of the system requires that the static attributes such as the geometry of the road network and preferably also at least some attributes related to the road network are available to service developers. At present, only few countries such as Finland and Sweden provide comprehensive digital maps of their own road networks as a publicly available data set. On the other hand, private companies such as navigation service providers and digital map providers (e.g. TomTom and Google) already have digital maps of the road network, historical data on travel times and possibly also real-time traffic information and enhanced map data for several member states. Usually, drivers have to manage several different goals such as time pressure, safety and comfort when choosing the route from origin to destination. This means that drivers willingness to comply with the recommendations provided by the service in real-life situations should be investigated further. Research projects ECOMOVE project has a subprojects SP3 ecosmart Driving and SP4 ecofreight and Logistics in which prototypes of the service are developed. The service is a research topic also in USA. University of Illinois has a project (Green GPS) which is developing a prototype system based on OBD-II data and a digital map. 4.6 Dynamic traffic light optimization and optimum speed advisory Description Dynamic traffic light optimization has been defined by Klunder et al. (2009) as: The objective of Dynamic traffic light synchronization based on actual traffic conditions is to optimise journey times and delays in urban, signal controlled, networks by controlling in real-time the green-times, cycle times and offsets (green waves) of the network s junctions. In the simplest case (the one and a half generation urban traffic control (UTC) systems, e.g. SIEMENS TASS), the UTC central controller switches between fixed-time plans based on traffic measurements received around the whole network. Also, local actuation may imposed, where the aforementioned fixedtime plans are locally and slightly modified based on local traffic measurements (e.g. the green times of specific road segments are slightly reduced or extended based on the presence or absence of vehicles in that particular segment. The second generation UTC systems such as SCOOT, SCATS, UTOPIA and TUC involve real-time optimisation and/or control techniques in order to optimise the green-times, cycle times and offsets of all network s junctions; the aforementioned quantities are updated on a second-by-second or on an once-every-cycle basis. A new cooperative service can be formed when dynamic traffic light optimization is combined with advice on optimal approaching speed provided to the driver. The traffic light system will predict the time to green and calculate a recommended speed to obtain a green light. This information is then communicated to the in-vehicle units and provided to the driver. The traffic light system may also broadcast the time to green signal to in-vehicle systems which then calculate optimum approaching speed profiles for vehicles. For example in the system under development in the COSMO (Cooperative systems for Sustainable Mobility and Energy Efficiency) project, the legacy traffic light system will predict the time to green 26

27 for approaching buses and calculate a recommended speed to obtain a green light, which will be communicated to the on-board unit (COSMO, 2010). The FREILOT integrated service allows for the optimisation of a traffic control system according to the presence of goods vehicles equipped with an acceleration/speed limiter, so that these vehicles even if taking more time to achieve cruising speed would arrive at the next signal in time to receive a green light. The traffic management element of FREILOT will optimise the traffic control system to reduce heavy vehicle fuel consumption. (FREILOT consortium, 2012) At present, there are several projects working with the service but there is no common definition which covers all systems with a similar functionality. For this reason, a new definition is proposed for dynamic traffic light optimisation and optimum speed advisory: The service combines dynamic traffic light optimisation with advice on optimal approaching speed provided to the driver. The traffic light system will predict the time to green and calculate optimum speed for vehicles approaching the intersection. This information is then communicated to in-vehicle units and presented to the driver. The traffic light system may also predict the time to green and communicate this information to in-vehicle unit which then determines the optimal approaching speed profile for the vehicle. The service may be provided at isolated intersections and in networks consisting of several signalised intersections equipped with network-level traffic optimisation features. The next step from providing advice to the driver is to utilize the current and predictive information on traffic light status as an input to the cruise control system of the vehicle. Use of traffic light status information and predictive information by vehicle cruise control systems has been discussed at a concept level by Behrang and Asadi (2011). The system presented in the paper utilizes information broadcasted by traffic signals to determine the optimum speed profile for a vehicle approaching the intersection. The objectives of the control algorithm presented in the paper are timely arrival at green light with minimum use of braking, maintaining a safe distance between vehicles and maintaining a constant or nearly constant cruising speed. Impacts Currently available information on the impacts of the system is based on simulations which have been carried out to analyse the impacts of the system in some specific traffic situations or scenarios. According to results of a simulation study carried out in PRE-DRIVE C2X project, the system has potential to reduce fuel consumption up to 7% in a scenario with high traffic volumes and close to 100% fleet penetration (Katsaros et al., 2011). However, this estimate applies only to traffic situations where the service is relevant. Klunder et al. (2009) estimated that dynamic traffic light controlling would have potential to reduce CO 2 emissions in EU 27 by 2%. Deployment status and time horizon for large-scale deployment An enhanced bus intersection logistics system is under development in the COSMO project (Cooperative systems for sustainable mobility and energy efficiency) (COSMO project, 2012). The FREILOT project is also developing a system which allows optimisation of urban traffic control in 27

28 terms of energy consumption according to the presence of goods vehicles (FREILOT consortium, 2012). In other words, the system exists in the form of pilots and prototypes but not as a commercial product. The user acceptance of a system with comparable functionality (eco-driving assistance system providing optimum speed advisory at traffic lights) and users willingness to pay for it have been studied recently with a questionnaire answered by more than 5000 respondents from 11 European countries. The authors concluded that in general drivers have a positive attitude towards eco-driving assistance systems and see them as useful. They also remarked that the users acceptance for additional costs and willingness to pay for the systems is very limited. (Trommer and Höltl, 2012) Research projects A prototype of the system is under development in the COSMO (Cooperative systems for sustainable mobility and energy efficiency) project (COSMO, 2010). The FREILOT project is developing a system which aims to optimise urban traffic in terms of energy consumption according to the presence of goods vehicles (FREILOT consortium, 2012). DRIVE C2X project is developing Green light optimized speed advisory for field operational tests. The aim of the developed function is to reduce stop times and unnecessary acceleration in urban traffic situations to save fuel and reduce emissions. The driver is provided a speed advice to help him to find the optimal speed to pass the next traffic lights during a green phase. In case it is not possible to provide a speed advice, the remaining time to green is displayed. (DRIVE C2X, 2013.) 4.7 Cooperative adaptive cruise control Description Cooperative adaptive cruise control is an extension of the existing adaptive cruise control systems. Existing adaptive cruise control systems aim to maintain either a constant speed of vehicle in freeflow conditions or a constant distance to a vehicle the equipped car is following. Cooperative adaptive cruise control adds the element of wireless communication between cars to existing adaptive cruise control systems and allows more accurate longitudinal control of vehicles travelling in a queue. Impacts Cooperative adaptive cruise control (CACC) systems are in the stage of research and development. Results of a field test carried out in the US with 16 test drivers indicated that the drivers using the CACC system selected vehicle following gaps that were about half of the length of the gaps they selected when driving with an adaptive cruise control system without cooperative functionalities (Nowakowski, 2010). The authors concluded that the results indicated drivers to be likely to choose shorter headways enabled by CACC which will have a positive effect on lane capacity. Increases in lane capacity will lead to shorter travel times in situations in which the capacity increase is not assumed to induce new demand. However, no detailed assessment on effects of CACC in Europe has been carried out. 28

29 The system has also been assumed to reduce fuel consumption because vehicles equipped with the system drive close to each other with reduced headways and can be expected to have a lower aerodynamic drag coefficient. Deployment status and time horizon for large-scale deployment The system is in prototype stage. A functional prototype system has been demonstrated in the SARTRE project (Safe Road Trains for the Environment) (SARTRE, 2012), and tests have also been carried out in the US (Shladover et al., 2009). Potential barriers to the deployment of the system include the users willingness to pay (Nowakowski, 2010) and legal and liability issues (van Schijndelde Nooij, 2011). Prospects for deployment of the system depend on the solution of legal and liability issues, regulatory issues and finding a suitable business model for the service. There is also a need to gather more information about the impacts of the system. For these reasons, it is doubtful whether largescale deployment of the system will be possible until the end of Research projects A prototype of the system has been implemented and demonstrated in the SARTRE project (Safe Road Trains for the Environment) (SARTRE, 2012). 4.8 Intersection safety assistant Description Several intersection safety functions were developed in EU project INTERSAFE2. Wimmershoff et al. (2011) reported the following functional descriptions: The VW crossing assistant is designed for give-way-scenarios. It warns and intervenes with a brake jerk in case of a crossing vehicle, if the situation is potentially critical. The system is designed for registered public roads only (in its current form). Private driveways do not have a "main" street status. The system calculates the exact relative position between the car and the stop line. The necessary input data are provided [by] Lidar sensor (Hella IDIS) and Laserscanner in the infrastructure. The infrastructure Laserscanners can detect a vehicle from up to 100 m distance. The Laserscanners are able to detect all kinds of road users, especially cars, trucks and also cyclists but not pedestrians. If crossing traffic is detected and the crossing traffic s trajectory (that has right of way) intersects with the ego vehicle s trajectory simultaneously in time and space the collision risk has a not negligible probability. If there is a vehicle approaching from the right side, it will be ignored if the driver signals to turn right. The VW right-of-way / stop line assistant warns and intervenes with a brake jerk in case of a violation of the right-of-way rules and not respecting the stop sign rule, respectively. The system calculates the exact relative positioning between car and stop line and warns if the driver s approaching speed is too high. The data for the right of way / stop line assist function are obtained from stereo camera system and map. The system could be supported by infrastructure Laserscanners at the road-side. The right of way function is mainly designed for junctions with priority to the right which is likely in urban residential areas. The optical warning shows the direction of the approaching vehicle. 29

30 The BMW left turning assistance informs the driver about critical gaps in turning left at intersections and aims to avoid collisions during left turning based on warning and intervention with a brake jerk. The system is used at intersections without traffic light control. The topology of the intersection is presented as a digital map, which is combined with data from the Laserscanners and cameras. The system observes and takes into account only vehicles (cars, trucks, and motorcycles). The driver s intention to turn left is identified by monitoring the use of the left indicator, the speed of the vehicle (if it drops below 10 kph), exact position of the vehicle in the intersection (if possible), and by trying to detect a left turning arrow on the road surface using the camera fitted in the vehicle. If the left indicator is not activated, the system will not be in operation. In the case that the system s risk assessment concludes that a collision is unavoidable, the brake is activated automatically and the driver is informed visually on the head-up display and with an acoustic warning. This safety feature can be bypassed by pressing the brake pedal or applying kick-down on the throttle. The system can also be switched off manually by pressing a button. VW right turning assistance for cars has a special focus on safety for vulnerable road users like pedestrians and cyclists during right turning manoeuvres. It warns and intervenes with a brake jerk if a vulnerable road user is in the right blind spot during right turn. This system only works at intersections, which provide a lane-level intersection map. However for intersections with complex geometry additional infrastructure Laserscanners are used to track VRUs on the cycle paths. The intersection topology, right of way regulations and the position of stop lines is registered in the map. In addition, the objects are delivered by the IDIS Lidar, by infractructure Laserscanners and short range radar sensors mounted on the right side of the car. If the traffic light is green and oncoming traffic is detected and the trajectories of cyclists intersect with the host vehicles trajectory the same warning strategy will be applied. The system works on every intersection with map data. However, when approaching the intersection the driver needs to switch on the right indicator. Right turning assistance for trucks has a special focus on safety for vulnerable road users (VRUs) like cyclists during right turning manoeuvres across the separate VRU paths. Right turning assistance for trucks warns the driver if a VRU is in the right blind spot during right turn. The system does not distinguish between pedestrians and cyclists. The system provides the driver with information about VRUs in the vicinity and warning about a VRU in the critical path both visually and acoustically. The region of interest is defined as the region on the right of the vehicle where a conflict with a VRU occurs during the manoeuvre (overlapping contours in predicted positions). The warning is a combination of a flashing LED in the right A-pillar and a warning sound. In addition, the all-aroundview camera system allows the driver to understand the reason for the warning by examining the blind spot. Impacts Wimmershoff et al. (2011) estimated that all section safety systems have safety benefits. The leftturning, stop line and intersection assistance functions showed the most substantial impacts on reducing fatalities and injuries by However, all systems were estimated to suffer from the expected low vehicle fleet penetration and infrastructure coverage. With expected penetrations rates for 2030 safety impacts of the different systems on fatalities were estimated to be equal or less than 1.3% and on injuries less than 2.7%. In full penetration the impact on intersection fatalities was % and on intersection injuries %. The effect on all fatalities was % and on all injuries %. 30

31 Wimmershoff et al. (2011) assumed that it probably would not be reasonable to bring to the market single intersection safety systems but rather a system combination having all the possible features. The analysis of safety impacts in full penetration revealed that the combination would have an impact of 9% on fatalities and 17% on injuries in EU27 in full penetration. The safety effects are the most in Northern and Central Europe (-15% and -23%), more than double compared to those in Southern Europe. The effects in Eastern Europe are somewhat bigger than in Southern Europe. As the intersection systems are aimed to improve the intersection safety, no research is available on the possible environmental effects of the systems. Deployment status Intersection safety systems are in the stage of research and development. It has been estimated that market penetration of all the intersection safety systems would be very low in 2020; only % of new passenger cars and 0.5-8% of heavy vehicles coming to market would have the system. Research projects Intersection safety systems were developed in two sequential EU projects: INTERSAFE which was a subproject of PReVENT and INTERSAFE-2 ( ). European project INTERSAFE2 developed a cooperative intersection safety system. Four different systems were developed in INTERSAFE2: red light or stop line assistant, left turn assistant, crossing assistant and right turn assistant. (Wimmershoff et al., 2011) High-level description from driver point of view An illustration of cooperative intersection collision avoidance system has been provided by US DOT (Figure 3). Figure 3. Illustration of cooperative intersection collision avoidance system (U.S. Department of Transportation, Research and Innovative Technology Administration, 2013). 4.9 Start-stop assistant Description Start-and stop systems automatically shut down and restart a vehicle s internal combustion engine to reduce the engine s idling time. The operating principle of any start-stop assistant systems is as follows: when the vehicle comes to a stop, the engine is automatically switched off. In the case of manual transmission, this will take place once the gear level is in neutral and the clutch pedal has been released. To restart the engine, the driver needs to activate the clutch. In the case of automatic transmission, the engine switches off after the brake pedal has been depressed. To restart the engine, the driver needs to take his foot off the brake pedal. (Katirtzidis, 2011.) 31

32 Impacts According to Hemphill, Schaeffler Group USA s vice president, with a manual transmission, a stop/start system can reduce fuel consumption between 2% and 5% in city driving, while an automatic transmission with stop/start can boost efficiency between 4% and 8% in the city (Murphy, 2011). According to a literature study carried by Klunder et al. (2009), the estimated effects of stop-andstart systems on the CO 2 emission reductions were in the range of 4-6% for all road types and traffic conditions combined. It was estimated that in urban areas the reduction would be in the range of 8-15% and in highly congested areas the start-stop system would help to reduce as much as 15-25% percent of the CO 2 emissions. Deployment status Start-and-stop systems have been under development since 1970s. The first versions in 1980s were too expensive. Today at least 15 car manufactures have stop-and-start systems in their vehicles (Wikipedia, 2013). The deployment status of the system has been studied as a part of the icar Support project. About 16.18% of new cars registered in 2011 in EU27 (3.79% in 2010) have been estimated to be equipped with a start-stop assistant (van Calker and Flemming, 2012a; van Calker and Flemming, 2012b; Öörni and Mäurer, 2012). Research projects The system is already a commercial product. Most of the research and development related to the system is carried out as product development by car manufacturers and their suppliers Tyre pressure monitoring system Description A definition for tyre pressure monitoring system based on (Klunder et al., 2009) is proposed: A tyre pressure monitoring system alerts the driver when the vehicle s tyres are below their ideal pressure. It is generally an electronic system designed to monitor the air pressure inside all the pneumatic tyres on automobiles and other vehicles. These systems report real time tyre pressure information to the driver of the vehicle - either via a gauge, a pictogram display, or a simple low pressure warning light. Most pressure-sensor based systems have a two-stage warning approach. The first driver notification is to show that the tyre is a little under-inflated - and so should be pumped up at the next opportunity. The second warning is more important - it is to signify that the tyre is dangerously under-inflated. Names Tyre pressure monitoring system (TPMS), tyre pressure indicator and Tyre Pressure Indication System (TPIS) are also used for the system. Impacts Vehicles with properly inflated tires consume less fuel, have longer tire life, and emit less carbon dioxide than vehicles with under inflated tires. Klunder et al. (2009) estimated that a type pressure monitoring system would decrease CO 2 emissions in EU27 by 1.2%. They stated: The system has a positive effect only if the drivers react correctly on the information given by the system. The emission 32

33 estimates are based on the potential effect when everybody reacts to the system immediately and correctly. In practice, for lower compliance there will be a smaller effect. Deployment status In 2007, the use of a tyre pressure monitoring systems was mandated in the U.S. (Toshiba, 2013.). Tyre pressure monitoring systems will be mandatory on all new passenger vehicles to be sold in the EU after November 2012 (European Commission, 2009b). Also in Japan and China, TPMS legislation is being reviewed (Toshiba, 2013). Therefore, the TPMS market is expected to expand in the near future (Toshiba, 2013). Research projects The system is available as a commercial product. Most of the research and development related to system is carried out as product development by system and component suppliers. High-level description from driver point of view Two pictures used to provide an illustration of the system are provided in Figure 4. Figure 4. Illustration of tyre pressure monitoring system (U.S. Department of Transportation, 2013) Cooperative local danger warning Description The system detects hazards such as obstacles or hazardous road and weather conditions via invehicle sensors. This information is then communicated to other vehicles using vehicle to vehicle communication technologies. The messages may be received directly from the originating vehicle or routed in a vehicular ad-hoc network. The message is then presented to the drivers approaching the hazardous location. A short definition for the system is proposed below (adapted from Wilmink et al., 2008): The system detects hazards such as obstacles and hazardous road or weather conditions via its own in-vehicle sensors and communicates the hazard information to other vehicles via vehicle-to-vehicle communication. Messages are exchanged with oncoming traffic and by networking (hopping). The messages are kept alive in a road-network for some time and distance. Also, information from the 33

34 roadside (road works, roadside units, etc.) can be integrated via infrastructure-to-vehicle communication. Only drivers approaching the hazardous spot will get the warning. The system provides drivers with the opportunity to adapt the vehicle speed and inter-vehicle distance early-on, leading to a higher situational awareness of potential unforeseen danger. The system is designed primarily for non-urban roads. Impacts Wilmink et al. (2008) estimated that a cooperative local danger warning system, when applied to all vehicles, would decrease the number of fatalities in EU25 by 4.5% and injuries by 2.8%. Deployment status Wilmink et al. (2008) estimated that in Europe in 2020 the penetration rate of a cooperative local danger warning for light vehicles would be 2-4% and for heavy vehicles 3-10%. Research projects In the EU project PReVENT a wireless local danger warning called WILLWARN was developed. EU project FOTsis (2013b) develops function Safety Incident Management (Figure 5) which general objective is to provide real time embedded information to drivers that warns them on any given situation that may reveal associated dangers or risks and that has been detected from elements in the infrastructure. FOTsis has selected among real-time danger warning services the following three particular items: tailgating alert, access speed in particular points and driver warning, and warning of difficult driving conditions due to adverse weather or other incidents. Figure 5. Safety incident management, FOTsis project (FOTsis, 2013b). DRIVE C2X project is deploying cooperative technologies in several European test sites. The following cooperative local warnings are deployed: obstacle warning, car breakdown warning, weather warning, slow vehicle warning, traffic jam ahead warning, approaching emergency vehicle warning, and road works warning. This effort will create a harmonized Europe-wide testing environment for C2X technologies. (DRIVE C2X, 2013.) 34

35 4.12 Wrong way driving warning Description Cooperative wrong way driving warning provides information of a vehicle travelling to wrong direction creating a hazard to other road users. Presence of a vehicle travelling to wrong direction is detected by a roadside monitoring system. Most commonly used technologies to detect ghost drivers are cameras combined with machine vision algorithms or video surveillance by a human user. Information on the presence and location of a vehicle travelling to wrong direction is then communicated to approaching vehicle by roadside ITS stations using V2I communication technologies such as IEEE802.11p. Upon receiving a warning, the in-vehicle system warns the driver with an audible sound or by other means. Current systems detect situations when the vehicle travels or is about to travel to wrong direction and warn the driver. However, this information is not communicated to other vehicles or infrastructure by existing systems. Cooperative wrong way driving warning is included as an use case in the ETSI Basic set of applications defined in ETSI TS (ETSI, 2010), and an illustration of likely the technical architecture of the system has been provided in (Malone et al., 2011) (Figure 6). Roadside ITS station (with detection of wrong way driving) DENM broadcast from other ITS station TCC Roadside ITS station - Communication and control unit (needed for I2V communication) - Data processing unit with software support for wrong way driving warning service - Capability to send DENM messages - Authorization from the road operator - Some roadside ITS stations: capability to detect vehicles travelling to wrong direction - Possibly: support for remote activation of wrong way driving from warning from TIC or TCC and provision of information to TIC or TCC DENM broadcast from originating vehicle Roadside ITS station DENM retransmissions by other ITS stations In-vehicle system (vehicle ITS station): - Communication and control unit (needed for I2V and V2V communication) - Data processing unit with software support for road works warning service - Information display and audio components - Satellite positioning receiver - Digital map and interface for map updates (with valid directions of traffic) - Capability to receive, store and forward DENM messages - Capability to warn the driver (suitable HMI) - Capability detect situations in which vehicle travels to wrong direction Back-office - Provision of digital maps to in-vehicle devices (Vehicle ITS stations) - Collection and processing of digital maps (including direction of travel) - Interface for map updates and maintenance of digital maps - Note: updates to in-vehicle devices may be carried out online using a data connection or offline using a USB stick or other suitable media Standards: Basic set of applications, Functional requirements (use case UC018): ETSI TS Decentralized Environmental Notification Messages, message format: ETSI TS GeoNetworking: ETSI TS Physical layer of data transmission: ITS-G5A (5.875 GHz to GHz), ETSI ES , IEEE802.11p Security architecture: ETSI TS Figure 6. Wrong way driving simplified technical architecture (Malone et al., 2011). Impacts Because of the novelty of the system no studies on the impacts of the system were found with a literature study. The system can be expected to be most effective for head-on collisions on motorways and other two-carriageway roads. 35

36 Deployment status The international automotive supplier Continental has developed a system that recognizes the risk and warns the driver if he is entering a highway in the wrong direction or is going the wrong way on a one-way street (Continental, 2012). Mercedes-Benz launched in 2013 a new traffic sign assistance system which uses a windscreen-mounted camera to search for no-entry signs and alerts driver through an acoustic and visual warning on the on-board electronics, when the vehicle is about to pass through incorrect carriageway. The data received from the camera is compared with data from the navigation system in a bid to enhance reliability of the system. The system is expected to be offered in the new Mercedes-Benz S Class, which is due to be launched in 2013 and the in the facelifted Mercedes-Benz E Class. Being initially designed for use in Germany, the Mercedes-Benz is working on deploying the system for use also in other countries as well as in other models. (Automobile Technology, 2013; Newcomb, 2013.) A prototype of a system providing a cooperative wrong-way driving warning has been under development (Lin 2011) and evaluated (Khoudour et al., 2011) in the CoVeL project (Cooperative Vehicle Localisation for Efficient Urban Mobility) (CoVeL, 2013). The project also outlined a perspective for a deployment roadmap (Figure 7). Research projects Figure 7. Perspective for deployment roadmap for the CoVeL platform (Mortara 2011). The requirements of the system for in-vehicle, roadside and back-office ICT infrastructure have been analysed in the SMART63 project (Malone et al., 2011). Wrong-way driving warning was also one of the use cases of the CoVeL project (Cooperative Vehicle Localization for Efficient Urban Mobility). High-level description from driver point of view High-level illustration of the operation of the system is presented in Figure 8. 36