EUROPEAN COMMISSION DG RTD - TRIMIS...EUROPEAN COMMISSION DG RTD SEVENTH FRAMEWORK PROGRAMME THEME 7 TRANSPORT - SST SST.2008.4.1.1: Safety and security by design GA No. 233942 ASSESS

EUROPEAN COMMISSION

DG RTD SEVENTH FRAMEWORK PROGRAMME

THEME 7 TRANSPORT - SST

SST.2008.4.1.1: Safety and security by design GA No. 233942

ASSESS Assessment of Integrated Vehicle Safety Systems for improved

vehicle safety

Deliverable No. ASSESS D2.1

Deliverable Title D2.1-R-PU-Integrated methodology framework-ASSESS-Final-v2-Andreas Lüdeke-14102010

Dissemination level

Public/Confidential/Restricted PU

Written By Jan Dobberstein (UoC), Mike McCarthy (TRL), Andreas Lüdeke (BASt)

14.10.2010

Checked by Helen Fagerlind (Chalmers) Christian C. Mayer (DAI) Carmen Rodarius (TNO) Andrés Aparicio (IDIADA)

30.08.2010 25.08.2010 13.08.2010 28.07.2010

Approved by Paul Lemmen 14.10.2010

Accepted by EC 2011-03-11

Issue date 2010-10-14

ASSESS D2.1 – Integrated socio-economic impact assessment framework

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Acknowledgement Following participants contributed to this deliverable report. Company Representative Chapters BASt Andreas Lüdeke All chapters UoC Jan Dobberstein All chapters TRL Mike McCarthy Executive Summary, Chapter 1


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Executive summary

The aim of the ASSESS project is to develop test and assessment methods for Integrated vehicle safety systems (IVSS) which combine elements of active and passive safety. In this project, methods for forward-looking collision avoidance and mitigation systems for passenger cars are being developed. A critical aspect of WP2 (Socio economic evaluation and legal aspects) of the ASSESS project is measuring the benefits conferred by the forward-looking safety system. The objective is to provide a thorough assessment of the safety impacts and, by comparing monetary valuations of the safety impacts with the investment and implementation costs of the systems, offering a cost benefit assessment. In this deliverable, the methodological framework and the tools for the socio-economic assessment of the safety systems are provided. This report describes the methodology developed to estimate the casualty benefits of the system and, in conjunction with system costs, the procedures to obtain estimated Benefit-cost ratios (BCR). The limits for the assessment shall be 2020 and 2030. The casualty benefits will be measured by predicting the reduction of the number of fatalities and injured road users in EU-27 accidents brought about by system fitment. The assessment shall also include the benefits of avoided congestion caused by accidents. For those accidents which are still occurring, albeit at a lower severity, the mitigation potential shall be estimated considering reductions in casualty severity. The procedure proposed for WP2, and how this links with other areas of the ASSESS project is presented in Figure 1. The safety potential (target population of casualties which could be influenced assuming full system fitment) will be estimated by WP1 (Definition of targets and final verification) and estimates of system effectiveness in specific test conditions will be delivered by the work packages carrying out testing activities: work package 3 (Evaluation of behavioural aspects), work package 4 (Pre-crash evaluation) and work package 5 (Crash evaluation). The work carried out within WP2 has resulted in the following proposals for the assessment of the safety effects and safety impacts in the ASSESS project:

• WP2 will consider estimated direct casualty benefits and also estimates for the congestion benefit from accidents avoided or reduced in severity.

a. The scope of study will be the fitment of the system to EU-27 passenger cars. b. The target casualty population information (provided by WP1) will be

combined with testing information (WP3/4) to estimate safety benefits. WP5 data will be used to validate injury reduction estimates.

c. The target casualty population will consider all casualties from the relevant accidents (provided by WP1).

d. Benefits will be estimated continuously up to two limits: 2020 and 2030. • In the socio-economic assessment in WP2 it is proposed to use the following:

a. Data on the vehicle stock and mileage will be provided by the ProgTrans European Transport Report 2007/2008 for all EU 27 Member States for 2020. Further extrapolated data will be used up to 2030.

b. In order to calculate the safety benefits, the share of equipped passenger cars does not give an accurate prediction of the real safety impacts of the systems. Normally the mileage of new passenger cars is higher than the mileage of older cars. Thus the fleet penetration of new equipped cars rates has to be converted into the share of the mileage by using data about age distribution of the car fleet and the age distribution of annual car kilometres. System cost


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estimates will be obtained via a literature survey for data on pre-crash system costs and retail prices. Validation of the cost estimation is proposed in conjunction with project partners from Daimler, Toyota, Bosch and TRW.

c. The forecast will be based on the following three scenarios: low, medium and high penetration rates.

d. All benefits and costs will use 2010 prices and specific proposals are presented; future costs and benefits will be discounted. A discount rate of 3% is proposed, although this will be reviewed in the light of recent economic conditions.

In addition to the proposed approach listed above, several important steps need to be developed further in WP2 and/ or agreed in the ASSESS consortium:

• Relationship between EU-27 high level statistics and the data from WP1 to develop procedure for “scaling up” accident data to EU-27 level.

o The time series will be based on the fatality trend from 1991 to 2008 by using EUROSTAT, CARE and IRTAD data.

• Agreement on the specific casualty valuations and congestion valuations to be used in the benefit assessment.

• Agreement on what type of system cost should be included in the study; should these be costs to the OEM or the end-user retail price?

• Due to the strong and complex relationship of WP2 with WP1, and the test results of WP3, WP4, and WP5 an assessment specific workshop will be planned that agrees on the safety impact model and its boundaries, the assessment framework, the decisions of assessment and preliminary socio-economic assessment results.

This report has also highlighted that important information is still missing although required for the proposed WP2 methodology:

• An agreed injury risk function or relationship to relate the performance of the system found in the ASSESS testing to the resulting casualty severity.

The following process diagram outlines the main components of the proposed WP2 methodology and illustrates the interaction with other work packages of the ASSESS project. Based on the result from all tests within ASSESS the safety impacts are assessed in WP2 (red dashed box) and a cost-benefit assessment is done:

ASSESS D2.1 – Integrated socio

Figure 1: Proposed ASSESS socio-

interactions (purple = WP1, orange

Integrated socio-economic impact assessment framework

-economic assessment method showing work package information

orange = WP3, WP4, WP5, blue = WP2)

assessment framework

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economic assessment method showing work package information


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Contents 1 Introduction .................................................................................................................... 9

1.1 Objectives and scope of the report .......................................................................... 9

1.2 Selected vehicle safety systems .............................................................................. 9

2 Review of existing socio-economic evaluation frameworks ............................................12

2.1 Overview of sources evaluated in survey ...............................................................12

2.2 Sources reviewed ...................................................................................................12

2.3 Summary of results of literature survey ..................................................................14

3 Data set .........................................................................................................................17

3.1 Accident data .........................................................................................................17

3.1.1 Accident data requirements of collision avoidance and mitigation systems .....17

3.1.2 ASSESS based in-depth accident data ...........................................................18

3.1.3 Macroscopic level accident data: The eIMPACT project ..................................21

3.1.4 Driver and driver behavior data .......................................................................23

3.1.5 Accident data forecast to year 2020 and 2030 ................................................23

3.2 Vehicle fleet and traffic data ...................................................................................25

3.3 Cost data ................................................................................................................25

3.4 Market data ............................................................................................................26

3.4.1 Market diffusion of considered pre-crash and brake assist systems ................26

3.4.2 Ranges of market penetration offered by “Beyond NCAP Assessment Protocol” ........................................................................................................................26

3.4.3 Forecast of fleet penetration rates ...................................................................27

4 Impact assessment methodology ..................................................................................29

4.1 Scope of impact assessment ..................................................................................29

4.1.1 Safety impact assessment ..............................................................................29

4.1.2 Congestion impact assessment (Indirect traffic impacts) .................................30

4.2 Theoretical and empirical methods for safety impact assessment ..........................30

4.2.1 Desktop research vs. empirical safety impact testing ......................................30

4.2.2 Characteristics of previous studies on safety impact assessment....................31

4.3 Impact assessment approach of ASSESS ..............................................................33

4.3.1 Role of WP2 and connection with other work packages in ASSESS ...............33

4.3.2 Overview about methodological approach of ASSESS ....................................36

4.4 Risk analysis for safety impact assessment ...........................................................43

4.5 Additional input for impact analysis and internal agreement on impact assessment methodology for ASSESS .................................................................................................44

4.6 Summary of safety impact assessment model in ASSESS .....................................44

5 Socio-economic assessment methodology ....................................................................47

5.1 General assumptions of assessment ......................................................................47

5.2 Benefit assessment ................................................................................................47

5.2.1 Evaluation methods for safety benefits ............................................................47


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5.2.2 Elements of accident costs ..............................................................................48

5.2.3 Cost-unit rates .................................................................................................49

5.3 Vehicle cost assessment ........................................................................................50

5.4 Cost-benefit analysis (CBA) ...................................................................................51

5.4.1 The method .....................................................................................................51

5.4.2 CBA process ...................................................................................................52

5.4.3 Benefit-Cost results .........................................................................................52

6 Risk Register .................................................................................................................55

7 Conclusion ....................................................................................................................56

8 Literature .......................................................................................................................57


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Tables Table 2-1: Sources evaluated in ASSESS survey .................................................................12 Table 3-1: Extract of the definition of variables for the accident database enquiry that could influence the performance of a pre-crash system .................................................................20 Table 3-2: Penetration rates and share of passenger mileage for Emergency braking system (BAUM, H. et al., 2008) ........................................................................................................26 Table 3-3: Car fleet diffusion scenarios ................................................................................27 Table 4-1: Accident scenarios selected for testing (ASSESS deliverable D4.1) ....................35 Table 5-1: Cost-unit rates for fatalities and injured persons ..................................................50

Figures Figure 2-1: Clustering of studies in literature survey .............................................................14 Figure 3-1: Accident causation and prevention model (own figure) .......................................18 Figure 3-2: Factors of accident severity (own figure) ............................................................20 Figure 3-3: One-dimensional distribution of background variables over all relevant accident classes, EU-27 (2005) (based on Wilmink, I. et al., 2008) ....................................................22 Figure 3-4: eIMPACT methodological approach for road safety prediction for 2010 and 2020, EU-25 (Wlmink, I et al., 2008, p. 37) .....................................................................................24 Figure 4-1: Methodological development of impact assessment of IVSS (own picture).........33 Figure 4-2: Overall system assessment (own figure) ............................................................35 Figure 4-3: Methodological multilevel process of socio-economic impact assessment: Tasks and interactions of WP2 with other WPs ...............................................................................37 Figure 4-4: Model of accident mitigation (based on AUST, M.-L., et al., 2010 .......................40 Figure 4-5: Impact V-model of using test results for estimation (own figure) .........................43 Figure 4-6: Process of safety impact assessment .................................................................45 Figure 5-1: Evaluation methods (ABELE, J. et al., 2005, p. 74, modified) .............................48


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1 Introduction

1.1 Objectives and scope of the report

The aim of the ASSESS project is to develop test and assessment methods for Integrated vehicle safety systems (IVSS) which combine elements of active and passive safety. In this project, forward-looking collision avoidance and mitigation systems for passenger cars are considered. These procedures shall be offered to EuroNCAP. By improving information available to consumers about active safety systems, individual benefits are more transparent and market penetration of the systems will be increased. Furthermore, specific components of the procedures may be used for future regulation to ensure minimum performance levels. A critical aspect of WP2 of the ASSESS project is measuring the benefits conferred by the forward-looking safety systems. The objective is to provide a thorough assessment of the safety impacts, and by comparing monetary valuations of the safety impacts with the investment and implementation costs of the systems, offering a cost benefit assessment based on the results of all testing in ASSESS. In this deliverable, the methodological framework and the tools for the socio-economic assessment of the safety systems are provided. The assessment of the safety system will focus on the accident avoidance and mitigation potential of the safety systems. Safety impacts of the system will be measured by the predicted reduction of the number of fatalities and injured road users in the EU-27 should the system be fitted to passenger cars. The accident mitigation potential shall be shown by a shift of fatal accidents to injuries, and of severe to less severe injuries. The limits for the time period over which the socio-economic assessment will be made, shall be 2020 and 2030. Direct traffic impacts like travel time reductions are not included into the analysis because they are expected to be marginal with respect to the safety systems considered in the ASSESS project. Indirect traffic impacts, as a result of avoided congestion from a reduction in road accidents, are considered to be relevant, and therefore included in the assessment. The functionalities of the safety systems evaluated are briefly described in Chapter one. Chapter two discusses socio-economic frameworks which have been carried out by previous projects to ensure that the approach taken by ASSESS is appropriate and builds on previous successful methods. Chapter three highlights the requirements of WP2 for accident data, system cost data, vehicle fleet and fleet penetration data. Chapter four provides background information on impact assessment methodologies and also describes the impact assessment methodology proposed by WP2 of the ASSESS. Chapter five describes the methodology and assumptions proposed for the ASSESS socio-economic assessment. 1.2 Selected vehicle safety systems

In ASSESS, test procedures for pre-crash and collision mitigation systems that are already on the market, are being developed. Based on the Pre-Crash sensing and brake assist systems from TOYOTA and DAIMLER, a generic system description is used as foundation for the socio-economic assessment. The description comprises the system application area, system functionality, and limitations of the systems. This fundamental scenario description allows a realistic assessment of the measured effects based on all testing in ASSESS.

1. Application areas: relevant accident scenarios In principle, the application scenarios of the IVSS considered in ASSESS are accident avoidance and mitigation in frontal direction. The analysis of accident frequency and severity presented in Deliverable 1.1 has identified the following accident scenarios as most relevant:


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• Accident in longitudinal traffic: Conflict between road user moving in same and opposite direction

• Turning-off/ Turning-in and Crossing accidents: o A turning-off accident occurs when there is a conflict between a turning road

user and a road user coming from the same direction or the opposite direction. This applies at crossings, junctions of roads and farm tracks as well as access to properties or parking lots.

o A turning in / crossing accident occurs due to a conflict between a turning in or crossing road user without priority and a vehicle with priority. This applies at crossings, junctions of roads and farm tracks as well as access to properties or parking areas.

2. Functionality of pre-crash and sensing systems The system description differentiates during the pre-crash phase between whether the collision is probable (a) or highly probable (b) or unavoidable (c). The basic functionalities of a Pre-Crash sensing and Brake Assist system are as follows:

(a) Possible collision: o A sensing system (based on a radar, infrared, or camera system) detects

position, speed and headway of a (target) vehicle or obstacle in front. Combining this information with vehicle speed, steering angle, vehicle yaw and lateral acceleration of the subject vehicle the collision risk is calculated.

o In case of a detected critical rear end collision situation, the Brake Assist automatically pre-fills the brake system. Thus, if the driver starts braking, the braking power is immediately fully available.

o In case of probable collision a warning display, tone, lamp or haptic signal is activated to warn the driver and direct his/her attention to the critical situation. The driver gains valuable time in decision making and reaction to prevent the collision or at least to reduce impact speed by braking. In addition, the Brake Assist supports the driver by increasing braking power.

(b) Highly probable collision: o If the driver reacts to the warning and the brake pedal is strongly depressed,

the brake assist function activates to increase the braking power, such that the crash is avoided.

o In addition, also for the case that the driver does not react sufficiently strong the braking is increased.

(c) Collision unavoidable: o In case the driver does not react, emergency braking activates braking power

automatically with maximal effort. o In addition, passive safety systems like the seatbelt are retracted to prepare

the occupants for a collision, airbags are activated, and sunroofs are closed. Some systems provide this function already if the collision probable.

In sum, monitoring crash parameters prior to the crash can be used to gain valuable time in decision making and to perform intelligent safety actions. This offers the opportunity to improve restraint systems such as seat belts, pre-tensioners and air-bags in terms of their response to the conditions, and perhaps to also reduce the costs of parts of the systems.

3. Limitations of the systems

o The functioning of the sensors may be impaired for example by a) dirt on the sensors, b) heavy rain, snow and hail, c) interference by other radar, or d)


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intense sunlight. In these conditions the detection capabilities of the sensors might be reduced.

o Depending on the viewing angle of the used sensors, e. g. radar, the function can lose track of the vehicle ahead in (narrow) curves.

o The sensing systems in the ASSESS project are not designed for the detection of pedestrians and other vulnerable road users.

This paragraph has shown 1) the target population of those conflict scenarios that current active safety systems influence, 2) the technical features reacting during the different stages of the driving conflict situation and 3) the boundaries reducing the effectiveness of the system. In ASSESS these topics are addressed by defining pre-crash test scenarios (WP 4) according to the analysed accident data, a virtual testing environment for the evaluation of the driver behaviour (WP 3) and sled tests with mitigated accident parameters (WP 5), thereby providing empirical and reproducible results about the functionality and effectiveness of the safety system.


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2 Review of existing socio-economic evaluation frameworks

2.1 Overview of sources evaluated in survey

A review of existing socio-economic evaluations was undertaken to ensure that the approach used by ASSESS embraces the most successful methods used in recent research approaches on the safety impact assessment of pre crash safety systems. This review covered 16 studies and reports of research projects. The main objective was to get an overview about methodological approaches for socio-economic assessment of vehicle safety systems and the effectiveness evaluation of pre-crash sensing and brake assist systems. This literature review provides the basis for the development of an assessment framework for the socio-economic safety impact assessment in the ASSESS project. The following section presents the literature survey template which was used to collect information in a systematic way. The template covers items with respect to the general methodology applied in the study, input data used, the single assessment steps, and the final results. Finally, an evaluation of the reviewed study with respect to completeness, validity of results, and applicability of the approach to ASSESS is provided. The literature surveys for each individual source are presented in the Appendix of D2.1. 2.2 Sources reviewed

The sources which are included in the survey are listed in Table 2-1. The different sources of the literature review can be clustered according to the focus of the studies:

• Methodological approaches: Included are pure methodological studies on socio-economic and safety impact assessment in general, and examples of assessments of vehicle safety systems.

• Analysis of technical performance and system effectiveness: Included are specific studies of active vehicle safety systems which affect collisiom types which are in the focus of the ASSESS project (e.g. rear-end collisions).

• Quantitative assessment results: Included are studies with numerical results on efficiency assessment (Benefit-cost ratio) and safety assessment (e.g. avoided accidents, causalities).

Table 2-1: Sources evaluated in ASSESS survey

Study Significant reference

SAFESPOT SAFESPOT – BLADE: Business models, Legal Aspects, and Deployment: Report on socio-economic, market and financial Assessment, 2009, Deliverable 6.5.1, Final Report (PDF)

eIMPACT eIMPACT: Socio-economic Impact Assessment of Stand-alone and Co-operative Intelligent Vehicle Safety Systems (IVSS) in Europe, Deliverable 6, 2008, Final Report (PDF)

CODIA CODIA: Co-Operative systems Deployment Impact Assessment, 2007, Deliverable 5, Final Report (PDF)

ECORYS/COWI ECORYS: Cost-benefit assessment and prioritisation of vehicle safety technologies, 2006, Final Report (PDF)

FESTA FESTA: Socio-economic impact assessment for driver assistance systems, 2008, Deliverable 2.6, Final Report (PDF)

SEiSS SEiSS: Exploratory Study on the potential socio-economic impact of the introduction of Intelligent Safety Systems in Road


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Vehicles, Final Report

iCars iCars Network: Catalogue of impact assessment methods for intelligent vehicle systems, 2010, Deliverable 3.5, Progress Report (PDF)

EU CBA European Road Safety Observatory: Cost-benefit analysis, www.erso.eu, 2006

TRL-AEBS TRL: Automated Emergency Brake Systems: Technical requirements, cost and benefits, 2008, Project Report (PDF)

NHTSA-FOT NHTSA: Evaluation of an Automotive Rear-End Collision Avoidance System, 2006, Project Report (PDF)

ACCIDENT COSTS BASt/ University of Cologne: Ermittlung der volkswirtschaftlichen Kosten der Straßenverkehrsunfälle in Deutschland, 2010, internal report

TRACE TRACE: Evaluation of the safety benefits of existing Safety Functions, 2008, Deliverable 4.2.2, Deliverable Report (PDF)

DAIMLER/Schittenhelm H. Schittenhelm: Design of effective collision mitigation systems and prediction of their statistical efficiency to avoid or mitigate real world accidents, 2008, FISITA-Paper F2008-08-109

TOYOTA H. Aoki, M. Aga et al.: Development of a safety impact estimation tool for advanced safety technologies, 2009, EVS 2009

GDV M. Kuehn, T. Hummel, J. Bende: Benefit estimation of advanced driver assistance systems for cars derived from real life accidents, 2009, EVS 2009

BOSCH A. Georgi, M. Zimmermann et al.: New approach of accident benefit analysis for rear end collision avoidance and mitigation systems, 2009, EVS 2009

VOLVO/ UMTRI M. Ljung Aust, T. Gordon et al.: Requirements and data sources needed for validation of component properties and performance in simulation based benefit assessment of driver assistance technologies, 2010

Figure 2-1 shows the clustering of the studies according to their primary research objectives. For example, the study results of the EU-projects FESTA, SEiSS, and iCars provide socio-economic assessment methodologies for different types of vehicle safety systems. Applications of these socio-economic assessment methods are provided by the CODIA, and SAFESPOT reports on cooperative vehicle safety systems. Different approaches for assessment of technical performance and effectiveness assessments of collision avoidance and mitigation systems, for example, are offered by the Daimler, Bosch, GDV, and TOYOTA studies. With exception of the TOYOTA study also numerical estimates on system effectiveness are provided. The NHTSA-FOT study provides safety assessment evaluations of combinations of Adaptive Cruise Control (ACC) systems with Front Collision Warning (FCW). Thus, the technical focus of these study is similar, but the specific vehicle safety systems addressed in ASSESS are not tested. But, this study is still included because of their innovative methodological approaches.

ASSESS D2.1 – Integrated socio

Figure 2-1: Clustering of studies in literature survey

2.3 Summary of results of literature survey

Cost benefit analysis is a core element to provide information on the socioefficiency of the impacts and concept of monetizing all related impacts and costs of system and accidentwell as generic economic data related to the analysed accidents in an objective perspective. If all the necessary information is available, the analysis is carefully conducted and documented, this allows a transparent and objective judgement; this principle should be followed by ASSESS. However, very often required data is unavailable and reasonable assumptions are required to conduct the assessment. Crucial points identified in the review were the following:

• Assessment method for system effectiveness: the effects of safety systems on different accident types and accident severities were estimated in varying some studies used retrospective accident or field data, others used predictive numerical simulations or relied on great variation in the validity of the effectiveness evaluations in the studies expected.

• Accident data base: Only a few countries (e.g. UK, Germany, or Sweden) possedatabases which contain sufficient information about detailed accident characteristics, such as accident and injury causation, avoidance action, etc., expressed in metechnical values. Even initem of information necessary to describe the complex effects of an active safety system which operates in different critical driving and accident phases (e.g. warning,assistance and intervention), particularly in relation to the exact timing of events and actions in the accident sequence.

Integrated socio-economic impact assessment framework

: Clustering of studies in literature survey (own figure)

Summary of results of literature survey

Cost benefit analysis is a core element to provide information on the socioefficiency of the impacts and costs of an IVSS. This quantitative method is based on a concept of monetizing all related impacts and costs of system and accidentwell as generic economic data related to the analysed accidents in an objective perspective.

cessary information is available, the analysis is carefully conducted and documented, this allows a transparent and objective judgement; this principle should be followed by ASSESS. However, very often required data is unavailable and reasonable

s are required to conduct the assessment.

the review were the following:

Assessment method for system effectiveness: the effects of safety systems on different accident types and accident severities were estimated in varying some studies used retrospective accident or field data, others used predictive numerical simulations or relied on desktop research and expert estimation. Thus a great variation in the validity of the effectiveness evaluations in the studies

Accident data base: Only a few countries (e.g. UK, Germany, or Sweden) possedatabases which contain sufficient information about detailed accident characteristics, such as accident and injury causation, avoidance action, etc., expressed in metechnical values. Even in-depth databases (e.g. GIDAS, OTS) do not contain every item of information necessary to describe the complex effects of an active safety system which operates in different critical driving and accident phases (e.g. warning,assistance and intervention), particularly in relation to the exact timing of events and actions in the accident sequence.

assessment framework

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Cost benefit analysis is a core element to provide information on the socio-economic costs of an IVSS. This quantitative method is based on a

concept of monetizing all related impacts and costs of system and accident-specific data, as well as generic economic data related to the analysed accidents in an objective perspective.

cessary information is available, the analysis is carefully conducted and documented, this allows a transparent and objective judgement; this principle should be followed by ASSESS. However, very often required data is unavailable and reasonable

Assessment method for system effectiveness: the effects of safety systems on different accident types and accident severities were estimated in varying ways. While some studies used retrospective accident or field data, others used predictive

expert estimation. Thus a great variation in the validity of the effectiveness evaluations in the studies is

Accident data base: Only a few countries (e.g. UK, Germany, or Sweden) possess databases which contain sufficient information about detailed accident characteristics, such as accident and injury causation, avoidance action, etc., expressed in measured

depth databases (e.g. GIDAS, OTS) do not contain every item of information necessary to describe the complex effects of an active safety system which operates in different critical driving and accident phases (e.g. warning, assistance and intervention), particularly in relation to the exact timing of events and


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• Market penetration rates: Because of the relatively long life cycle of cars, uncertainties in the economic development and future development in road safety measures, predictions about the market diffusion of IVSS are very difficult. Therefore, the market deployment of IVSS is often described in the studies with the help of different scenarios to cope with these uncertainties. By using scenarios for a range of possible penetration rates of IVSS, and corresponding safety and traffic impacts, a range of benefit-cost ratios results is produced.

The following previous conclusions based on the findings of the different research approaches shall be emphasized:

• The EU-projects on vehicle safety systems eIMPACT, CODIA and SAFESPOT provide guidance on data sources that are available, and how the calculation of the overall benefits, costs, and efficiency of the evaluated systems may be integrated in a holistic framework.

• However, the safety system specification of the ASSESS project and the scope of impact assessment deviates from the previous mentioned EU-projects. For example, the former projects concentrate on accident avoidance. Assessment of mitigation of accident consequences as an additional research objective of ASSESS, for example by reduction of impact speed, requires a modified approach. For the development of an enlarged and modified assessment methodology the methodological studies SEISS and FESTA will be used as guidelines.

• To optimise the quality of the results and provide a statement on the stability of the estimated safety effects and benefit-cost ratios, complementary analyses are recommended. For example, the influence of parameter variations on the calculated results should be taken into account by a sensitivity analysis.

• Only a few studies analyse the interdependences and interferences between

different technical functionalities of pre-crash sensing systems and driver reaction in detail. This seems to be very important for systems which only vary in detail, e.g. by the determined sequences of a safety measure if the system detects a critical situation. It is important for the comparison of often very different solutions of safety systems to understand exactly which system functionality is responsible for which change in e.g. speed reduction, brake reaction time etc.

• For scaling up the results to the EU-27 level, the established data sources e.g. provided by the eIMPACT project can be used. For the estimation of effectiveness of different types of brake assist systems, the results achieved by DAIMLER, BOSCH, GDV and TRL-AEBS which are based on a more precise definition of accident target population compared to the eIMPACT project should be considered in addition for ASSESS.

• A few studies such as the CODIA or TOYOTA study on Safety Impact Methodology

(SIM) consolidate statistical accident data to numerical models by simulation of traffic and environmental conditions. As a result, checking the effects e.g. of enhanced braking performance in a virtual environment is possible. This approach can be considered as an option for gaining a detailed understanding of the complex interactions of active safety functions as well as for filling in blank spots in data material, such as missing accident data for eastern European countries.


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• The quantitative results on system effectiveness and safety impacts yet available from previous assessments provide a starting point for a preliminary assessment of the IVSS which are subject of the analysis in ASSESS:

o Results from the TRL-AEBS, eIMPACT, DAIMLER and GDV studies deliver remarkable safety potential and positive benefit-cost ratios for the relevant brake assist systems: the relatively high frequency of rear-end crash scenarios enable the regarded systems to provide a high safety benefit.

o As mentioned above, most of the studies rely on retrospective data and apply predictive approaches for the system effectiveness parameters. This is an appropriate approach for systems fitted to vehicles which are not yet found in sufficient numbers in the accident population.

• The survey provides insights into the technical specifications of the IVSS and

corresponding effects of specific accident scenarios. Results on the capabilities and limits of the systems have implications for the system specific aspects of the assessment method for ASSESS:

o As a result of the literature survey, a differentiation between ACC with FCW, Emergency Brake Assistant (EBA), Automated Emergency Braking System (AEBS) and future systems (e.g. cooperative solutions, combinations with lateral-active systems) is necessary, as well a detailed technical classification by system and scenario parameters.

o Since the studies reviewed use different data sources (accident data bases) or are carried out at different points in time a detailed technical classification for system and scenario parameters has to be conducted.

• There are a lot of studies available for ASSESS estimating the future benefits of active

safety systems. But the orientation of these studies only partly matches the approach of the socio-economic assessment in ASSESS.

• There is no equivalent model in the literature for the task of transferring pre-crash test results (outcome of WP4 of ASSESS) into system effectiveness and safety benefits.

Thus, a methodological gap has to be closed in the project, since on the one hand the tests offer a very detailed understanding of the pre-crash situation, while on the other hand the socio-economic assessment aims on estimations on the macroscopic level:

• First of all, the geographic scope of EU-27 requires a method to fill data gaps and inconsistencies in the data as accurate as possible, for example, by clustering countries and assuming similarities between known and unknown accident patterns, as was done e.g. in eIMPACT project.

• But most important, in ASSESS a general methodology for assessment has to be developed which integrates data about the detailed working of the safety system derived from all testing within ASSESS with their consequences on accident avoidance or mitigation. According to the impact assessment, technically focused approaches (especially the studies of TRL, Bosch, DAIMLER and NHTSA), will contribute to the WP2 methodology by providing detailed and accurate information about the real effects of the systems.


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3 Data set

3.1 Accident data

3.1.1 Accident data requirements of collision avoidance and mitigation systems

To determine the safety benefits of the safety systems described in chap. 1, an accident database is required to show the accident avoidance and mitigation potential of the safety systems. For this the target population of accident types must be identified. In the following, the target population is defined as the number of casualties that could be prevented by a system that is 100 % effective in each of the accident situations it is intended to influence. This number can also be expressed as a percentage of addressed accidents. Thus, the target population shows some hypothetical maximum possible safety impact of the system. WP 1 of ASSESS provides input on the accident target population by Deliverable 1.1 and 1.2. In the future, later generations of these systems will most likely be able to address collisions with other vehicles, obstacles, and vulnerable road users. WP2 develops a framework for the socio-economic evaluation of these safety systems. In ASSESS, the socio-economic assessment framework will be applied to collisions of passenger cars with other four-wheeled vehicles. In order to develop an accident data set to be able to show reliable safety impacts of the evaluated safety systems, the accident data needed for assessment has to fulfill a range of requirements:

1. The accident data used must be in-depth such that sufficient information exists to closely define the accidents which may be influenced by the systems (target population).

2. The accident database should contain data to enable assessment of the known functional limitations of the systems which will influence the system effectiveness in avoiding or mitigating accidents (for example weather conditions).

3. The accident database should be representative, or appropriately scaled up to approximate as closely as possible, the road accident situation on the EU-27 level.

Points 1 and 2 above demand for an accident data set which is detailed enough to differentiate between accident types, impact velocities, injury levels and environmental conditions like weather, road type, and so on. Detailed information about injuries of persons involved in the accident and environmental conditions during the accident are collected in in-depth accident data bases. The level of detail of most in-depth databases is considered sufficient to get all necessary information needed to derive all available test parameters for the relevant accident scenarios. In ASSESS in-depth data from the UK and Germany is provided by WP1. In addition, national accident data from Great Britain and Sweden is analyzed to provide a check that the findings of the detailed level were sufficiently representative of a larger population. The problem of in-depth data is that only a low number of accidents is included such that the data base may not be representative for all accidents in the country, and especially not for accident distribution on the EU-27 level. To provide a proof of the representativeness of the results, European road accident data provided by the eIMPACT / TRACE project based on the CARE data base will be used. eIMPACT / TRACE provides accident types similar to the one used in ASSESS thus a comparison of the frequencies will be done. If large deviations are observed then a range of safety assessment results (e.g. optimistic vs. pessimistic values) will be provided. With respect to general accident data considering the number of fatalities at the EU-27 level, the accident statistics of EUROSTAT provides data. In addition, these data will be used to forecast the fatalities and injuries for the assessment period 2020 to 2030.


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To transfer the possible safety impact on the target population to a realistic safety impact driver simulator, pre-crash and crash tests are used in ASSESS. In addition, desktop analysis provides validation of the test results. The test results will provide data to assess the effectiveness of the systems for preventing and mitigating accidents and causalities. However, by using tests the problem of transferring test results to reality can arise, such that the validity of the test results is reduced. In principle, the experimental design of the test scenarios based on the accident scenarios cannot cover all relevant factors which can possibly influence performance of the systems because of limited resources. In addition, the in-depth data will not entail all relevant factors which influence the accident situation and the technical performance of the systems. For example, parameters of driver behaviour near to and in the crash situation are difficult to find in the accident data. Therefore, some additional figures are needed for adjustments of test results, for example on driver fitness with respect to “sleepiness”, “distraction” and “alcohol/ drugs” and for driver behaviour within the last few seconds before an accident,. The driver simulator tests in WP3 and the figures about driver fitness and distraction provided in deliverable D3.1 will provide some indication in this respect. 3.1.2 ASSESS based in-depth accident data

Given the above restrictions of point 1 and 2, a data inquiry was formulated in WP2 with respect to accident data to be provided for the assessment of WP2. The data inquiry comes out of a model of accident causation and prevention shown in Figure 3-1. Driver behavior like distraction and/ or critical environmental conditions like impaired visibility have an impact on about whether a critical driving situation arises and results in a collision in the end. The functionalities of the pre-crash systems intervene in the critical accident situation, in order to avoid the collision or mitigate its consequences. However, the effectiveness of the pre-crash systems in the critical traffic situation is also influenced by driver behaviour and environmental conditions.

Performanceof safety system

Vehicle (wo./w. Pre-Crash System)

Reaction

Behaviour

•Braking•Steering•None

•Distraction• Impairment

Conflict/ initial situation

Driver

Environmental/situational conditions

Light

Road

Weather

Accident consequences

Performanceof vehicle in conflict

Speed:•Pre-Impact

•Lateral offset

•Collision type

Accident severity:•Number fatalities•Number of serious, slight injured

Model of accident severity• Impact speed• Injury risk function• Impact avoided?•Type

•Conditions

Figure 3-1: Accident causation and prevention model (own figure) The above crash model as an essential part of the safety impact and benefit assessment can be broken down into several sub-models. Each of these sub-models summarise the specific data requirements about the crash and the environmental conditions linked to it:


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• In the centre of the crash model is the vehicle without the active safety system installed. It enters a conflict situation which is defined by initial conditions and shows a certain “performance” during the pre-crash phase which results in a crash (at least for the case without the active safety system).

• The driver (as focused in detail in WP3) which is the key factor for the performance of the safety system has to be modelled by average and typical parameters for driver behaviour.

• Environmental conditions may cause a crash (driving on a wet road, aquaplaning, and irritations by sun, etc.) or influence the conflict (e.g. water or mud on the road prolongs the braking distance).

• The above mentioned factors show interactions between vehicle, driver and environmental conditions in each conflict resulting in a crash. Depending on these interactions different accident consequences and accident costs are the result of the crash. The accident consequences measured by different scales and only differentiating roughly between fatalities and injured persons cannot be used to show variations of accident mitigation by the safety systems alone. To get an aggregate value for accident mitigation, an index such as injury risk functions will be applied.

In addition to the influence on the accident consequences the mentioned conditions on the side of the driver and the situational conditions may affect the actual effectiveness of the safety system in the conflict situation (“with IVSS case”). For example, a distracted driver may not react to a warning signal issued, or critical environmental conditions like impaired visibility negatively influences the technical performance of the system. So there are two main reasons, why it is important to gain more information about the environmental situation of the crash as well as of the involved vehicle-driver-system:

• Representative test setup: when estimating the system effectiveness that derives from the ASSESS pre-crash tests, there has to be a clear understanding, whether the environmental conditions assumed for the test (weather, road, driver behaviour and fitness) vary within the accident target population. Since the ASSESS tests are executed under laboratory e.g. repeatable and controlled conditions, this additional analysis is necessary for extrapolating the acquired results on the “whole situation”.

• IVSS limitations: specific environmental conditions may cause problems for the system performance resulting in impaired system effectiveness.

To sum up, for the representativeness of the test set up mentioned above, information is needed from WP1 about the distribution of crashes related to the multi-dimensional environmental conditions, driver and vehicle behaviour and accident parameters. Given this set-up, the pre-crash and accident mitigation system is applied to the accident population. Assuming that the conflict situation for the “with-out IVSS” case always ends in a crash, two possible outcomes result when the IVSS affects the crash (“with IVSS case”) (see Figure 3-2): Firstly the crash might be mitigated or secondly completely avoided. In the latter, the conflict would not appear in the accident statistics. Since one focus of the current generation of pre-crash safety systems is collision mitigation, one of the main parameters describing the accident is speed, more specifically impact speed. Hence, the speed distribution and devolution, which occurs between the point of entering a conflict situation and the not prevented crash, is one of the main interests when modelling accidents as a foundation for the assessment of active safety measures.


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Crash avoi-ded?

4

Accident type

Accident severity

Mitigated crash progress

Injury risk matrixImpact speed

Impact angle

Off-setVehicle with Pre-

Crash System

Vehiclespeed

Driver

Enviroment

Initial conflict

Accident severity•Number fatalities•Number of serious, slight injuries

Model of accident severity• In jury risk function

Yes

Mitigated & avoided crash consequences= safety benefit

No

Figure 3-2: Factors of accident severity (own figure) The analysis performed in WP1 has confirmed that turning-off, turning-in, crossing accidents and accidents in longitudinal traffic are relevant with respect to the pre-crash systems selected within the ASSESS project (see ASSESS Deliverable 1.1). In task 1.2 of WP1 the accident data bases are analysed in more detail also with respect to the situational accident variables and data requirements necessary for the assessment of WP2.

Table 3-1: Extract of the definition of variables for the accident database enquiry that could influence the performance of a pre-crash system

Category Variables Accident type

Type 2/3: Turning off accident / Turning-in/ crossing accident:

A turning accident occurred when there was a conflict between a turning road user and a road user coming from the same direction or the opposite direction (pedestrians included!). This applies at crossings, junctions of roads and farm tracks as well as access to properties or parking lots. A turning in / crossing accident occurred due to a conflict between a turning in or crossing road user without priority and a vehicle with priority. This applies at crossings, junctions of roads and farm tracks as well as access to properties or parking lots.

Type 6: Accident in longitudinal traffic

The accident in longitudinal traffic occurred due to a conflict between road users moving in the same or in the opposite direction.

Initial accident conditions

Vehicle speed Driving speed

Closing speed in longitudinal traffic

Environmental conditions

Weather conditions Rain

Snow

Hail

Lighting conditions Dazzling sunlight (Sunlight that directly shines into the


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eyes of the road user, which could have impaired vision.)

Driver type and behaviour

Crash avoidance manoeuvre Braking

Steering

Both

None

Driver fitness Influence of drugs or alcohol

Crash related faults

Degree of fatigue

Accident seriousness

Impact speed

Offset

Impact angle

Accident consequences

Numbers of Fatalities

Numbers of serious Injuries

Numbers of slight Injuries

3.1.3 Macroscopic level accident data: The eIMPACT project

The eIMPACT project assessed the socio-economic effects of twelve Intelligent Vehicle Safety Systems (IVSS) and their impact on traffic, safety and environment. Since the CARE data base is limited, especially because the collision type variable had been removed from the database, additional data was compiled in the eIMPACT/ TRACE project to get data on the needed level of detail for the EU-25. Therefore, in the eIMPACT / TRACE project a high level accident data base for EU-25 especially with respect to different collision types and environmental conditions was developed. The reference year of the accident data compiled was 2005. To extract the disaggregated data, an enquiry to national data bases was designed to match the data needs of the safety impact analysis with the available data. The enquiry was then sent to the respective countries via the TRACE project. For efficiency reasons, the countries of the EU-25 were then grouped into three different country clusters with a similar level of road safety performance based on the number of fatalities in 2005. For more details on the data compilation see ASSESS deliverable D1.1, and deliverable D4 of the eIMPACT project (Wilmink, I. et al., 2008). Figure 3-3 shows the resulting collision types by which accidents with causalities showing fatalities, seriously or slightly injured were analysed in eIMPACT to get estimates of safety impacts of the applications. Furthermore, the classification by road type, weather and light conditions and location (junction) was used to refine the accident structure. Regarding the conditions of each sub-accident and weighted by its frequency and severity type, the safety impact was assessed.


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1. Collision on the road with pedestrian

2. Collision on the road with all other obstacles

3. Collision beside the road with pedestrian or obstacle or other single vehicle accidents

4. Frontal collision

5. Side-by-side collision

6. Angle collision

7. Rear collision

8. Other accidents with two vehicles

9. All other collisions Figure 3-3: One-dimensional distribution of background variables over all relevant accident classes, EU-27 (2005) (based on WILMINK, I. et al., 2008) The selected sub-accident types of ASSESS for “Accident in longitudinal traffic – opposite direction and same direction” match very well with the CARE definitions for Rear and Frontal collisions, respectively, which are used in the eIMPACT project for safety impact assessment. The angle collision type of eIMPACT entails all collisions with side impact of target car and frontal impact of subject car. These are conflict types typically arising at junctions. The “Junction collisions” (turning off/ turning in accidents) selected for ASSESS resemble this CARE accident type also very well. To sum up, the SafetyNet and eIMPACT classifications of collision types are quite similar. Therefore, accident type frequencies calculated in the eIMPACT project for 2005 and for EU-25 level can provide orientation with respect to validity of the relevance of accident scenarios applied in the test scenarios of ASSESS. However, compared to the data set provided for ASSESS, the eIMPACT data has several limitations, especially for the analysis of system effectiveness with respect to mitigation of accident consequences. Important input variables for accident severity like vehicle speed, offset, and impact angle are not recorded. Moreover, information about the impact driver behaviour/ reaction has on the initial conflict situation is not provided by eIMPACT. Thus, the in-depth data used by ASSESS is essential for the safety impact assessment in ASSESS. Since problems with the representativeness of in-depth data for EU-27 can arise accident

11%

6%

13%

8%

5%

25%

13%

6%

13%13%

7%

22%

18%

2%

15%

5%3%

14%

0%

5%

10%

15%

20%

25%

30%

1 2 3 4 5 6 7 8 9

Injury accidents Fatalities


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data of the eIMPACT / Trace project shall be used to check the validity of ASSESS-in-depth data. 3.1.4 Driver and driver behavior data

The accident data analysis in ASSESS will not provide information on crash avoidance behaviour and driver fitness which is used for the test layouts. But, in the driver simulator and pre-crash tests a normal fitness of drivers is assumed. Therefore, the problem can arise that the assumptions for driver behaviour and reaction in the tests deviate from behaviour which a relevant fraction of drivers shows in “real” driving and accident situations. For example, driver sleepiness and use of alcohol/drugs during driving can have an important impact on road accidents. Available data from the literature on driver fitness and behavior therefore will be used to check whether the pre-crash test results deviate in a considerable way from the figures found in the literature. If it seems plausible that these deviation have an influence on the system effectiveness derived in the tests, adjustments based on the figures will be done. The literature survey and the figures provided by Deliverable 3.1 of ASSESS on sleepiness, distraction and alcohol/drug use will be used as a source. 3.1.5 Accident data forecast to year 2020 and 2030

Since up-to-date forecasts of accidents and/or casualties for the boundaries of the target period 2020 to 2030 are not available on EU-27 level, it is necessary to perform an own estimation of road safety indicators for the selected time horizon. In ASSESS the approach used in eIMPACT will be followed, where the road safety prediction for EU-25 was based on the future development of the fatality risk for different country clusters, i. e. the ratio between the total number of fatalities and the total vehicle kilometres driven. Data on vehicle kilometres driven were not available for some countries. In these cases the ratio between fatalities and the vehicle stock, being an indicator determining road safety, was calculated. Given these ratios time series of the annual number of fatalities and vehicle-km respectively vehicle stock per year for the period 1991 to 2005 were obtained for the 25 countries using the CARE and the IRTAD (International Road Traffic and Accident Database) databases. For each year of this period, the fatality risk was calculated. A time series analysis was carried out using exponential regression to extrapolate the trend of fatality rates to the year 2020. In a further step, the number of fatalities in each country cluster was calculated backwards by using values for vehicle kilometres driven or numbers of vehicles provided by recent forecasts for the target years.


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Figure 3-4: eIMPACT methodological approach for road safety prediction for 2010 and 2020, EU-25 (WILMINK, I et al., 2008, p. 37) Being based on accident data for the period 1991 to 2005, the forecast approach takes into account the effects of all measures taken for the improvement of road safety at any level in the EU within this time period. Hence, it is presumed for the road safety prediction that the already implemented measures will still be effective in the future and that no additional efforts are made to reduce the number of accidents and casualties. Using this assumption, the trend in fatalities will follow only the change in vehicle kilometres or vehicle stock. The injury data forecast was simply carried out by assuming that the ratio between fatalities and injuries in 2005 remains constant, and thus this ratio and the fatality forecast could be used for estimating injuries in 2010 and 2020. For accurate estimation of which impact the safety systems have on the number of accidents and connected causalities a clear distinction is needed for the case with and the case without the safety systems. Thus the estimated accident trend shall provide a basis which is affected by the safety systems. However, there are already brake assistant systems in 2010 or before introduced to the market, presumably on a low scale. For determination of the safety impact of systems in 2020 to 2030 a hypothetical situation without any collision avoidance and mitigation system has to be generated. Therefore, the accident trend which is used for the forecast has to be corrected by fatalities avoided by systems already on the road. For this, the actual penetration rate and that of a few years before is needed to establish a correction factor to calculate the hypothetical number of fatalities without any collision avoidance and mitigation systems.1 This penetration rate might be quite low, and the corresponding safety impact is almost zero, but this is yet to be proven. For the ASSESS project the eIMPACT approach has to be modified further as follows:

1 See BAUM et al (2009) for the calculation of such a correction factor for the socio-economic

assessment of an Electronic stability program for the period 2008 to 2012.


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• The data forecast will be extended to EU-27, thus incorporating the new member states of the European Union Bulgaria and Romania.

• The assessment period will be extended from 2020 until 2030. • The time series will be based on the fatality trend from 1991 to 2008 by using actual

EUROSTAT, CARE and IRTAD data. • The forecast of the trend on passenger car mileage will be based on the actual

ProgTrans European Transport Report 2007/2008. 3.2 Vehicle fleet and traffic data

To calculate the costs of the safety systems the total vehicle fleet of passenger cars equipped with the systems has to be estimated for the period 2020 to 2030. Therefore three main pieces of information are required:

• Stock of passenger cars • Total penetration rate of safety systems (whether the system was fitted) • Average “end user” cost-unit rate for each safety system.

Chapter 3.3 shows the approach of cost estimation of the pre-crash systems and chapter 3.4 shows the process of estimating of market diffusion of the systems based on market data. Data on the vehicle stock is provided by the ProgTrans European Transport Report 2007/2008. The report includes data from all EU 27 member states. The report entails a forecast of the stock of passenger cars for 2020, but not for the year 2030. For scaling up the fleet data for passenger cars until 2030 the fleet growth rate provided by the actual ProgTrans European Transport Report will be used. To calculate the safety benefits the share of equipped passenger cars does not give an accurate prediction of the real safety impacts of the systems. The mileage driven of new equipped passenger cars will be higher than the mileage driven by older cars. Thus the fleet penetration rates have to be converted into the share of the driven mileages. This will be done by weighting the distribution of the age distribution of the car fleet by the age distribution of annual car kilometres (WILMINK, I. et al., 2008). The ProgTrans European Transport Report 2007/2008 includes an estimate of person-kilometres of passenger cars of EU-27 for 2020, but not for 2030. The growth rate of passenger transport will be used to extrapolate the trend until 2030. 3.3 Cost data

In general, the elements of the costs of the safety systems are the following: • Manufacturing and implementation costs (investment costs) • Maintenance costs which depend on a system’s complexity and robustness. It will be

assumed that the safety systems are built for the full lifetime of the vehicle. The maintenance costs therefore involve mere fault repair.

• Operating Costs. Safety systems are active parts of the vehicle and therefore add mass and consume energy. Both of these can be translated into fuel consumption and then correlated to costs.

Whether there are significant operating and maintenance costs will be checked by asking the experts from the participating OEMs. In general, the cost data should include all resource use which is connected to production, installation, use and distribution of the safety system from the point of view of the society. The above mentioned cost items influence the end-consumer price of the system. Usually direct cost information are difficult to get such that retail price can be used as an estimation. If installation of system is optional in the car then a retail price of the system is directly


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available which could then be used for estimation. If the Emergency braking system is supplied as a package of a vehicle safety system, at least the fraction attributable to the Emergency braking system can be estimated. The estimation of vehicle safety system costs will be done by a

• Literature survey for data on pre-crash system costs and end-consumer prices of the systems. Also cost estimates available from other EU-projects on safety systems will be used (e.g. eIMPACT).

• Finally, a validation of the cost/ retail price estimation in cooperation with OEM project partners (DAIMLER and TOYOTA) and supplier (TRW) will be performed to ensure that the selected cost-benefit analysis is appropriate. Of course, it has to be considered for the estimation that most of the cost information is highly confidential. Therefore, only very rough estimations will be possible e.g. by providing a range of costs.

3.4 Market data

3.4.1 Market diffusion of considered pre-crash and brake assist systems

Because the pre-crash and brake assist systems are already on the market or near to the market, some country specific or vehicle model specific data on the market acceptance of considered systems will be offered, if possible. In addition, research will be done on available studies about acceptance or penetration forecasts of pre-crash sensing and brake assist systems.

For example, in the EU-project eIMPACT an emergency system was assessed with similar functionalities than in ASSESS. The eIMPACT project considers the years 2010 and 2020. For each year two scenarios are created: the “low” scenario and the “high” scenario. The low scenario means that there are no special incentives to get the system in the market. In this scenario the penetration rate follows the status quo development of the market. The high scenario considers the case that stakeholders give incentives to support the market take-up of the systems. An incentive can be for example that the safety systems are subsidised by lower taxes from the year x onwards. Thus, four penetration rates were estimated in eIMPACT: 2010 low, 2010 high, 2020 low, and 2020 high.

Table 3-2: Penetration rates and share of passenger mileage for Emergency braking system (BAUM, H. et al., 2008)

2010 2020 Scenario Low High low high Fleet 0 0 3.6% 8.2% Share of mileage 0 0 4.5% 9.9%

The penetration rates were based in eIMPACT on expert estimation. In a scenario workshop it was concluded, that the implementation of a new safety system usually takes 5 to 6 years for the new vehicles and an additional 15 – 20 years are needed to cover the whole fleet. Since during the running time of eIMPACT an emergency brake system was not on the market, therefore, for the year 2010 a penetration rate of zero was estimated. In a ASSESS a similar estimation procedure as in eIMPACT using a scenario approach will be applied. 3.4.2 Ranges of market penetration offered by “Beyond NCAP Assessment Protocol”

The problem of market penetration (“Potential level of dissemination”) of safety systems is also addressed in the “Beyond NCAP Assessment Protocol”. Under the subheading “Expected benefits/ side effects” there two criteria are provided which shall be used to score the expected dissemination level of the safety systems as part of a system evaluation. The first criteria refer to availability of the system and the second to the market shares:


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1. Availability: These criteria value systems according to their availability in the

different vehicle segments and variants and the applied fitment scheme: • Is the technology fitted standard on all variants in all markets? • Is the technology standard on all variants in EU-27? • Is it standard on best selling or high-end variant only? • Is it optional on all variants? • Is it optional on some variants only?

2. Market shares: The following ranges of expected sales volumes for qualifying the

expected benefits a vehicle safety system offers on the European scale are defined: • Are sales expected > 75.000 units/year? • Are sales expected > 50.000 units /year but ≤ 75.000 units/ year? • Are sales expected > 10.000 unit /year but ≤ 50.000 units/ year? • Are sales expected > 500 units/year but ≤ 10 000 units/year? • Are sales expected ≤ 500/year (small volume series according to EU).

Both NCAP criteria shall be used to characterise market penetration scenarios for the forecast of penetration rates in the passenger car fleet. 3.4.3 Forecast of fleet penetration rates

The forecast will be based on the following sketched three scenarios:

Table 3-3: Car fleet diffusion scenarios

1. Mandatory action

2. Complementary/ Supporting action

3. OEM strategy

For estimation of the penetration rates given the scenarios the approach described in eIMPACT will be used (ASSING, K. et al., 2006):

1. Mandatory action (very high diffusion speed): Starting point of the forecast is an estimation of the share of new cars of the complete European car fleet in 2015. For this, the trend in registration of new cars of the last 10 years

Installation is obliged in all new vehicles of all car segments from 2015 on (technology is standard on all variants)

E.g. awareness campaigns/ EuroNCAP, Financial incentives/ Tax rebates, Equipment of new vehicle of major fleet owners, EU action Safety system is provided also as an option in other car segments.

Market diffusion by making safety system standard in luxury car segment and cascading down to lower car segments

Technology is standard on all variants for all new vehicles in EU27.

Technology is standard on best selling or high-end variant only for all new vehicles. Technology is optional on all variants for all new vehicles.

Technology is standard on best selling or high-end variant only for all new vehicles.

Very high market diffusion speed

High market diffusion speed (depending on level and scope of actions)

Low market diffusion speed


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will be used (Data base for new passenger car registration: European Automobile Manufacturer´s Association (ACEA)). A constant share of new registered cars and duration for complete renewal of the car fleet of 15 to 20 years in 2030 will be assumed. Also a constant age distribution of cars of the fleet will be assumed. The estimation of the diffusion speed until the year 2020 will be based on experiences with safety measures becoming mandatory in all new vehicles like for example the seat belt.

2. Complementary/ Supporting action (high diffusion speed) The estimation will be based on (national/European) experiences with financial incentives like insurance rebates or tax subsidies to stimulate installation of safety systems, fuel saving or emission reduction technologies into newly registered cars. Important European or national incentive programs will be evaluated to derive estimations.

3. OEM strategy (low diffusion speed)

Starting point of the calculation is the share of new vehicles in the luxury car segment. It is assumed that the systems are then cascading down to lower car segments (e.g. after every renewal of vehicle model of 2 year). In Germany for example on average between 2006 and 2009 about 7% of newly registered cars belong to the luxury car segment. Thus, given a fraction of newly registered cars of about 9% of the complete fleet the equipment rate after one year of market introduction of the safety system is about 0.6% (9% x 7%). Assuming 10 car segments the system is standard in all newly registered cars after about 19 years. The statistics of the European Automobile Manufacturer´s Association (ACEA) will be used as data for new passenger car registration in different car segments. It will be assumed that the share of the car segments as observed in the last 10 years remains constant. Because the fleet penetration rates will have an important impact on the socio-economic assessment of the IVSS the approach for estimation of the penetration rates will be agreed on in the ASSESS consortium. After the estimation of the fleet penetration the penetration rates will be converted for the three scenarios into the share of driven mileage by weighing the vehicle age related fleet distribution with the vehicle age distribution of annual vehicle kilometers.


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4 Impact assessment methodology In this section the methodology of impact assessment and the specific approach of ASSESS will be explained. In general, the overall objective of ASSESS is to generate a functional and empirical impact assessment approach. While there are several studies estimating the impacts and benefits of IVSS using desktop results on safety effects (e. g. eIMPACT, CODIA, SAFESPOT), the methodology of integrating empirical data (e. g. FOT) into the assessment has still to be evolved further. This holds especially with respect to test results about crash avoidance and mitigation of real-world accidents which are addressed in ASSESS. In the following, first the scope of the impact assessment is described, and second a short overview of approaches for estimation of the collision avoidance and mitigation potential of vehicle safety systems is given. The ASSESS specific approach is explained in the third part of this section with special focus on application of test results on prospective accident data for safety impact estimation. In this section also the relation to the other work packages is highlighted. In the fourth part, methodological challenges of the impact assessment in ASSESS which is addressed by a risk analysis, and in the fifth part additional input to the impact assessment is explained. 4.1 Scope of impact assessment

The impact assessment will focus on safety impacts. In addition, avoided congestion as a side product of accident avoidance is included in the assessment (indirect traffic impacts). Direct traffic impacts like significant variations of travel time, fuel consumption and related environmental impacts presumably will not arise, and thus will not be part of the assessment. In general, direct traffic effects are not expected because the pre-crash and brake assist system will not influence average speed and driving distance etc significantly. 4.1.1 Safety impact assessment

The safety impacts are the starting point for calculating the safety benefits. To determine the safety impacts, at first the possible safety effects have to be identified. For example, the methodology developed in the eIMPACT project examines the functional chain of impacts from mechanisms to actual safety benefits. The approach for identifying safety effects aims to capture all possible effects of Intelligent Vehicle Safety System (IVSS) on driving behaviour and on accidents in a systematic manner. In addition to intended effects behavioural adaptation of the drivers is included in the assessment. In principle, such estimation can cover beside the accident risk also the exposure to accident risk during a trip and the modification of accident consequences by a reduced rescue time. The latter two factors are not relevant for pre-crash systems. First, the pre-crash safety system will not have an impact on route choice or choice of transport mode, and thus on risk exposure, and second, intelligent injury reducing systems for a quick and accurate crash reporting and call for rescue are out of the scope of this project. Hence, the relevant mechanisms which influence the accident risk and which are addressed in ASSESS are the following.

1. Direct in-car influence on the driving task: The pre-crash systems fitted to the cars evaluated in ASSESS will influence the driving task in different ways:

a. The collision warning informs the driver about a critical driving situation and will direct his/her attention to the critical situation.

b. In case of a detected critical rear end or frontal collision situation, the Brake Assist will make braking faster and stronger.


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c. If the accident is unavoidable, the automatic emergency braking reduces impact speed, which increases passive safety and reduces accident consequences.

The pre-crash tests which will be conducted within WP4 will deliver empirical data on direct performance of the pre-crash system. The driver behaviour will be investigated within WP3 and from the tests conducted within WP5 information on injury reduction can be derived.

2. Indirect modification of user behaviour: The driver can adapt to driving with the

pre-crash system. This is often called behavioural adaptation and will often not appear immediately after a change but may show up after familiarization with the system and is hard to predict. Behavioural compensation effects can arise such that concentration on the driving task is reduced and/ or more risky driving with more speed and less headway is induced. The effect has to be considered for determining the total system effectiveness. A desktop analysis will be done on estimations of the relevance of behavioural adaptation for the performance of Emergency braking systems.

4.1.2 Congestion impact assessment (Indirect traffic impacts)

The indirect traffic effects will be calculated using the changes in the number of accidents as reported by the safety impact analysis. Avoided accidents by the pre-crash sensing system can lead to benefits in terms of reduced congestion costs. Which magnitude of reduction in congestion costs can be expected from avoided fatalities and injuries will depend on the road types and periods of the day:

• In morning and evening peaks the traffic flows mainly consist of traffic that has high value of times such as commuters, and freight traffic. Economic damage due to considerable time losses is therefore likely to occur. In addition, fatal accidents will lead to considerable congestion on most motorways and some rural roads in peak hours. Also, in city networks high traffic loads will easily fill the area around the accident and consequently block other crossings. Even though most urban networks are quite dense, it is unlikely that traffic can be easily rerouted during busy periods.

• In off-peak hours, congestion may also arise due to fatal accidents. However, traffic in off-peak hours will have lower values of time, and the impact will be less because of lower traffic flows. In city centres traffic can more easily be rerouted through the dense network, leading to considerably less congestion costs.

• At night traffic volumes are very low, so no significant reduction in congestion is expected then.

• On motorways congestion costs will be much higher than on rural roads, because of the higher traffic flows.

The indirect traffic effects are calculated by using the estimated safety impacts. The accident data available in ASSESS for determination of accident scenarios (ASSESS D1.1, 2010) does not entail specific information about the distribution of avoided accidents over the day. Thus, average avoided congestion costs to estimate the indirect traffic will be used. The cost-unit rates used will be agreed in the ASSESS consortium. 4.2 Theoretical and empirical methods for safety impact assessment

4.2.1 Desktop research vs. empirical safety impact testing

The safety impact assessment in ASSESS aims at estimating the collision avoidance and mitigation potential of safety systems. Because the assessment is forward looking using a retrospective analysis based on accidents in the real world, e.g. a case-and-control approach, is not possible. Thus a predictive model is necessary which applies available


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results on system effectiveness on the forecasted accident target population. In principle, such a model can use expert estimations, simulation results, or results from FOTs and pre-/crash-tests as data source for estimation of system effectiveness. The different methods used by theoretical and empirical approaches with respect to data generation for impact assessment can be characterised as follows:

• Theoretical approaches: The safety system effect is determined by using elaborated physical models and simulations. Theoretical approaches can further include the usage of R&D data or tests, vehicle safety expert analysis and computer simulation results rebuilding the stochastic devolution of the different crash phases which allow estimation of safety impacts by application of reliable and validated previous scientific results. By desktop research the already available data and results are aggregated for example to the statement that system “A” can reduce x % of collisions of crash type “Y”. Desktop analysis can include empirical results e.g. based on driver simulator studies, pre-crash and crash tests.

• Empirical approaches: Usually the internal validity of theoretical approaches, i.e. the researcher’s ability to formulate accurate conclusions about the cause-and-effect relationships will not be very high. To improve internal validity of the safety impact assessment empirical foundation by small and large-scale FOTs, laboratory studies on driving simulator and test track is required. The quality of the data acquisition depends on the sampling techniques (e.g. random sampling) used and the research design (e.g. case and control approach). Of course, for the case of an ex-post assessment, also the method of accident data analysis is available, which allow to find and to prove correlations between the introduction of a safety measure in the past and the reduction in accident statistics – but up to now mainly in the field of passive safety. This statistical proof states the ideal scientific impact assessment, since the uncertainty of the results can be assumed to be low and the data situation to be reliable. However, for innovative vehicle safety systems making use of this approach is not possible.

The ASSESS approach combines theoretical and empirical research approaches. In the context of the ex-ante assessment of ASSESS the integration of empirical data in the assessment improves the situation considerably compared to assessments based only on desktop analysis. Nevertheless, no direct test of the systems in the field is done and the future impacts (and benefits) still have to be predicted. That means that part of the assessment still is theoretical research. The overall safety assessment however, can be improved further in quality and reliability, which will be shown in chapter 4.3. 4.2.2 Characteristics of previous studies on safety impact assessment

In addition to the summary on the literature survey given above in chapter 2, some crucial points regarding impact assessment of this survey shall be highlighted here (see Appendix 2.1):2

• The theoretical approaches are not concerned with the conflict between crash test parameters and detaile

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EUROPEAN COMMISSION DG RTD - TRIMIS...EUROPEAN COMMISSION DG RTD SEVENTH FRAMEWORK PROGRAMME THEME 7 TRANSPORT - SST SST.2008.4.1.1: Safety and security by design GA No. 233942 ASSESS