d2.1 – requirements and use cases - trimis · 2015-07-03 · watch-over project fp6-2004-ist-4...

Vehicle-to-Vulnerable roAd user cooperaTive communication and sensing teCHnologies to imprOVE transpoRt safety

D2.1 – Requirements and use cases Project contract n.: FP6-2004-IST-4 – 027014

Workpackage, workpackage title: WP2, User Requirements and Scenarios

Task, task title: T2.1, User Requirements - T2.2, Scenarios, Use Cases

Deliverable n.: D2.1

Document title: D2.1-Requirements and use cases

Deliverable type: PUBLIC

Document preparation date: 30.06.2006

Authors: A. Mousadakou (HIT), A. Guarise (CRF)

Consortium:

Centro Ricerche Fiat, DaimlerChrysler AG, Piaggio & C. S.p.A., Robert Bosch GmbH, MIRA

Limited, Technische Universität Chemnitz, ARC Seibersdorf research GmbH, Centre for Research

and Technology Hellas, University of Stuttgart, Steinbeis Stiftung für Technologie Transfer, Faber

Software S.r.l., LogicaCMG Nederland B.V., Università di Modena e Reggio Emilia

Project co-funded by the European Commission

DG-Information Society and Media

in the 6th Framework Programme

WATCH-OVER Project FP6-2004-IST-4 – 027014 PUBLIC

D2.1-Requirements and use cases

This project has been co-funded by the European Commission DG-Information Society and Media in the 6th Framework Programme. The content of this publication is the sole responsibility of the project partners listed herein and does not necessarily represent the view of the European Commission or its services.

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Document Control Sheet Project name: WATCH-OVER

Workpackage, workpackage title: WP2, User Requirements and Scenarios

Task, task title: T2.1, User Requirements - T2.2, Scenarios, Use Cases

Document title: WATCH-OVER_D2.1-Requirements and use cases

Main author(s): L. Andreone (CRF), E. Bekiaris (HIT), A. Guarise (CRF),

A. Mousadakou (HIT)

Other author(s): E. Portouli (HIT)

M. Pieve, F. Galliano (PIAGGIO)

K. Meinken (USTUTT)

D. Gavrila (DC)

Date of submission to Consortium: 11.07.2006

Date of submission to European Commission: 27.07.2006

Revision history:

VERSION DATE AUTHOR SUMMARY OF CHANGES

1.0 31.05.2006 L. Andreone, A. Guarise First draft

1.1 01.06.2006 L. Andreone, A. Guarise Revision of document structure

2.0 05.06.2006 L. Andreone, E. Bekiaris, A. Guarise, A. Mousadakou, E. Portouli

First input

3.0 20.06.2006 L. Andreone Revision

4.0 26.06.2006 A. Mousadakou, E. Bekiaris Second input

5.0 27.06.2006 A. Guarise, A. Mousadakou Revision of document structure and section 2 and 4 and input on section 5

6.0 28.06.2006 L. Andreone Revision

7.0 10.07.2006 L. Andreone, E. Bekiaris, A. Guarise, A. Mousadakou

Revision of Section 4 and input on section 5

8.0 11.07.2006 A. Guarise Final draft version

8.1 14.07.2006

C. Ferrarini, L. Etzler, M.

Pieve, F. Galliano, I. Ducci, K. Meinken, D. Gavrila, U. Beutnagel-Buchner, A. Sikora

Revision and input

9.1 20.07.2006 L. Andreone, A. Guarise Final version for Peer review

10 26.07.2006 A. Guarise, A. Mousadakou Revision after Peer review report




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List of abbreviations ABS Anti-lock braking system AG Aktiengesellschaft AMA American Motorcyclist Association AVV Adviesdienst Verkeer en Vervoer BAST Bundesanstalt für Straßenwesen BIC Bicycles BMF British Motorcyclists Federation BV Besloten Vennootschap CARE Community Road Accident Database CAT Cars and trucks CBS Centraal Bureau Voor de Statistiek CRO Crossing CUR Curve DB Database EC European Commission ECMT European Conference of Ministers of Transport ETSC European Transport Safety Council EU European Union FARS Fatality Analysis Reporting System FEMA Federation of European Motorcyclists Association FIM Federation Internationale de Motocyclisme GES General Estimates System GIDAS Grafisch-Interaktives Datenanalysesystem GmbH Gesellschaft mit Beschränkter Haftung HMI Human Machine Interface HW Hardware ID Identifier IRTAD International Road Traffic and Accident Database IST Information Society Technologies ISTAT Istituto Centrale di Statistica LED Light Emitting Diode OEM Original Equipment Manufacturer OV Other Vehicle PED Pedestrian PCT Perpendicular crossing trajectories POT Parallel overtaking trajectories PTW Powered two-wheelers (motorbikes and moped) ROU Roundabout RTT Respective turning trajectories r(wg) Within-group agreement SA Situation awareness SPA Socità per azioni SQL Structured Query Language SRL Società a responsabilità limitata STR Straight road SW Software SWOV Stichting Wetenschappelijk Onderzoek Verkeersveiligheid Tx.y Task (number x.y) UC Use case VRU Vulnerable road user WPx Work Package (number x)




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Table of contents Document Control Sheet................................................................................................................... 2 List of abbreviations .......................................................................................................................... 3 Table of contents .............................................................................................................................. 4 List of Figures ................................................................................................................................... 5 List of Tables..................................................................................................................................... 5 1. Executive Summary .................................................................................................................. 7 2. Preliminary information ............................................................................................................. 8

2.1. Previous related projects................................................................................................... 8 2.1.1. The PROTECTOR European project ........................................................................ 8 2.1.2. The SAVE-U European project.................................................................................. 8 2.1.3. The MAIDS European project.................................................................................... 9

2.2. Review of accident data .................................................................................................. 10 2.2.1. Problem size............................................................................................................ 11 2.2.2. Pedestrians ............................................................................................................. 13 2.2.3. Bicyclists.................................................................................................................. 19 2.2.4. Powered two-wheelers ............................................................................................ 23

2.3. Initial list of scenarios ...................................................................................................... 29 2.3.1. Pedestrians ............................................................................................................. 29 2.3.2. Bicyclists.................................................................................................................. 32 2.3.3. Powered two-wheelers ............................................................................................ 33

3. Selection of Scenarios ............................................................................................................ 35 3.1. Scenarios from expert brainstorming .............................................................................. 36

3.1.1. Selection of new scenarios...................................................................................... 36 3.1.2. Prioritisation of scenarios ........................................................................................ 42 3.1.3. Identification of parameters ..................................................................................... 47

3.2. Scenarios from methodical analysis................................................................................ 49 4. User requirements................................................................................................................... 53

4.1. Questionnaire preparation............................................................................................... 54 4.2. Questionnaire results ...................................................................................................... 55

4.2.1. Respondents sample............................................................................................... 55 4.2.2. Requirements regarding system output................................................................... 58 4.2.3. Evaluation of scenarios ........................................................................................... 61 4.2.4. Suggestions from the respondents.......................................................................... 68

5. Selection of Use Cases........................................................................................................... 69 5.1. Scenarios final considerations......................................................................................... 69 5.2. Use cases description ..................................................................................................... 71

Conclusions .................................................................................................................................... 82 References...................................................................................................................................... 83




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List of Figures Figure 1: Road injuries and fatalities (CARE, EU-15 2002) ............................................................ 11 Figure 2: Road fatalities per one thousand of population in EU-25 (BAST 2003)........................... 12 Figure 3: Fatalities in 2002 in 14 EU countries (SAFETYNET Del. 1) ............................................ 13 Figure 4: Pedestrian-Vehicle accident configurations (Stanzel 2002) ............................................ 14 Figure 5: Collision speed (when known) in fatal accidents with pedestrians (FARS 2004) ............ 15 Figure 6: Number of pedestrian fatalities by hour of day, EU-14 2002 ........................................... 16 Figure 7: Number of pedestrian fatalities and injuries by hour of day (SWOV data 2003).............. 16 Figure 8: First contact point for vehicle-pedestrian accidents (SAVE-U Del. 1A) ........................... 18 Figure 9: Collision types according to SAFETYNET Del. 1 ............................................................ 19 Figure 10: Collision speed (when known) in fatal accidents with bicyclists involvement (FARS) ... 20 Figure 11: First contact point for vehicle-bicyclists accidents (SAVE-U Del. 1A)............................ 22 Figure 12: Collision types according to SAFETYNET Del.1 ........................................................... 23 Figure 13: number of PTW accidents related to a particular configuration (MAIDS 2004) ............. 24 Figure 14: PTW line of sight to Other Vehicle (MAIDS 2004) ......................................................... 28 Figure 15: Other Vehicle line of sight to PTW (MAIDS 2004) ......................................................... 28 Figure 16: Workshop prioritisation relevance for road safety.......................................................... 42 Figure 17: Workshop prioritisation relevance for the use of a cooperative approach ..................... 43 Figure 18: Relevance for road safety, comparison of mean value and r(wg) ................................. 44 Figure 19: Adequacy for cooperative system, comparison of mean value and r(wg) ..................... 45 Figure 20: Respondents’ gender distribution. ................................................................................. 55 Figure 21: Respondents’ age distribution. ...................................................................................... 56 Figure 22: Respondents’ years of driving. ...................................................................................... 56 Figure 23: Last year driven kilometres............................................................................................ 57 Figure 24: Percentages of the kilometres driven on different road types........................................ 57 Figure 25: Users’ preferences for information, if there is no accident risk. ..................................... 58 Figure 26: Users’ preferences for type of information, if there is no accident risk. ......................... 59 Figure 27: Users’ preferences for information means, if there is no accident risk. ......................... 59 Figure 28: Users’ preferences for location of visual information, if there is no accident risk........... 60 Figure 29: Users’ preferences for warning, if there is accident risk. ............................................... 60 Figure 30: Users’ preferences for means of warning, if there is accident risk................................. 61 Figure 31: Users’ willingness to have such a system. .................................................................... 61 Figure 32: Frequency occurrence of each scenario in real traffic situations. .................................. 62 Figure 33: Frequency occurrence of scenarios per VRU related category. .................................... 63 Figure 34: Evaluation of support needed in each scenario............................................................. 64 Figure 35: Evaluation of support needed in scenarios per VRU related category. ......................... 65 Figure 36: Level of system intervention required, per scenario. ..................................................... 65 Figure 37: Warning vs informing; respondents’ attitudes................................................................ 66 Figure 38: Car speed in which support is required, per scenario.................................................... 66 Figure 39: Time of the day in which support is needed, per scenario............................................. 67 Figure 40: Weather conditions in which support is needed, per scenario....................................... 67

List of Tables Table 1: Parameters considered in accident statistical survey ....................................................... 11 Table 2: Total number of fatalities per country (CARE, EU-15 2002) ............................................. 12 Table 3: VRUs fatalities based on German national data (2002-2004) .......................................... 13 Table 4: Vehicle manoeuvre in accidents with pedestrian involvement (FARS, GES from USA)... 15 Table 5: Fatal accidents involving pedestrians per body type of other vehicle (FARS) .................. 15 Table 6: Accidents involving pedestrians per body type of other vehicle (GES)............................. 15 Table 7: Accidents involving pedestrians in the US per lighting condition (FARS, GES)................ 17 Table 8: Accidents involving pedestrians in the USA per road condition (FARS, GES) ................. 17




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Table 9: Location of fatal accidents with pedestrian involvement (FARS) ...................................... 17 Table 10: Impact area on other vehicle for vehicle-pedestrian accidents (GES) ............................ 18 Table 11: Vehicle manoeuvre in accidents with bicyclist involvement (FARS, GES)...................... 20 Table 12: Fatal accidents involving bicyclists per body type of other vehicle (FARS) .................... 20 Table 13: Accidents involving bicyclists per body type of other vehicle (GES)............................... 20 Table 14: Accidents involving bicyclists in the US per lighting condition (FARS, GES).................. 21 Table 15: Accidents involving bicyclists in the US per road condition (FARS, GES) ...................... 21 Table 16: Location of fatal accidents with bicyclist involvement (FARS) ........................................ 21 Table 17: Impact area on other vehicle for vehicle-bicyclists accidents (GES)............................... 22 Table 18: Injuries and fatalities of bicyclists in Germany in 2004 ................................................... 23 Table 19: PTW manoeuvre in accidents with PTW involvement (GES).......................................... 25 Table 20: MAIDS results on PTW collision partner (MAIDS 2004) ................................................. 25 Table 21: PTW collision partner in accidents in US (GES 2004) .................................................... 25 Table 22: Illumination at time of accident (MAIDS 2004)................................................................ 26 Table 23: Light conditions in accidents with PTW involvement (FARS, GES) ................................ 26 Table 24: Road condition in accidents with bicyclists involvement in the US (FARS, GES)........... 27 Table 25: Traffic environment of fatal accidents with motorcycle involvement (FARS) .................. 27 Table 26: Impact area on other vehicle for accidents involving PTW (GES) .................................. 29 Table 27: Injuries and fatalities of occupants of powered two-wheelers in Germany in 2004......... 29 Table 28: Pedestrian accident survey outcomes ............................................................................ 30 Table 29: Proposed WATCH-OVER pedestrian-related scenarios................................................. 31 Table 30: Bicyclist accident survey outcomes ................................................................................ 32 Table 31: Proposed WATCH-OVER bicyclists-related scenarios ................................................... 33 Table 32: PTW accident survey outcomes ..................................................................................... 34 Table 33: Proposed WATCH-OVER PTW-related scenarios ......................................................... 35 Table 34: New "turning right" scenarios.......................................................................................... 37 Table 35: New bicycle scenario ...................................................................................................... 37 Table 36: New scenarios with obstacles......................................................................................... 38 Table 37: Selection of scenarios for the questionnaire submission ................................................ 41 Table 38: Technical feasibility......................................................................................................... 46 Table 39: Overview of the scenario relevance for different aspects .............................................. 47 Table 40: Accident opponents combinations .................................................................................. 50 Table 41: Accident opponents and type of road ............................................................................. 51 Table 42: Type of accidents considering category, type of road and relative trajectories .............. 51 Table 43: Parameters combination for type of accident.................................................................. 53 Table 44: Scenario suggested from questionnaire respondents..................................................... 68 Table 45: Ranking of scenarios gathered from questionnaire ........................................................ 69 Table 46: Revision of Table 43 for the WATCH-OVER framework................................................. 71 Table 47: Group of highly relevant scenarios ................................................................................. 72 Table 48: Group of medium relevant scenarios .............................................................................. 73 Table 49: Technological feasibility marks within the WATCH-OVER framework............................ 73 Table 50: Use case 1 description.................................................................................................... 74 Table 51: Use case 2 description.................................................................................................... 75 Table 52: Use case 3 description.................................................................................................... 76 Table 53: Use case 4 description.................................................................................................... 77 Table 54: Use case 5 description.................................................................................................... 78 Table 55: Use case 6 description.................................................................................................... 79 Table 56: Use case 7 description.................................................................................................... 80 Table 57: Use case 8 description.................................................................................................... 81




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1. Executive Summary The WATCH-OVER project started in January 2006. It is a specific targeted project co-funded by the European Commission Information Society Technologies (IST) in the strategic objective "eSafety Co-operative Systems for Road Transport". The goal is the design and development of a cooperative system for the prevention of accidents involving vulnerable road users in urban and extra-urban areas. The innovative concept is represented by an on board platform and by a vulnerable user module. The system is based on short range communication and vision sensors. WATCH-OVER intends to examine the detection of vulnerable road users in the complexity of traffic scenarios in which pedestrians, cyclists and motorcyclists are walking or moving together with cars and other vehicles. This document is the outcome of the project workpackage n. 2 activities on the definition of the “user requirements and of the scenarios and use cases” and highlights the most relevant information needed for the development of the WATCH-OVER system. This report is the basic and initial step for project’s technical activity. Considering as preliminary information previous related projects and the statistical analysis of road accident data, in section 2 a first set of scenarios is derived, listed as the most relevant for the safety of vulnerable users while they move in a road. WATCH-OVER experts consider that a single approach to the definition of the scenarios and use case would not be complete as from one side available data on road accidents are not giving a whole picture neither the level of details that are needed to define the relevant scenario and use cases; from the other side, a systematic approach alone would not guarantee that the assumptions made are fully adherent to the real situation. Therefore a multiple approach is followed in section 3. The outcomes from available results of previous projects available results and the survey of accident data are complemented with the analysis performed in expert brainstorming sessions and benchmarked with a systematic definition of the relevant scenarios, again defined by experts of the WATCH-OVER project. Additionally the list of scenarios is then submitted to a group of external experts / users (drivers, motorcyclists, cyclists and pedestrians) by means of a questionnaire for an evaluation of the most significant accident configurations, in section 4. The questionnaires are structured also to investigate the user needs that should be considered for the WATCH-OVER device. Questionnaires are divided into different parts, one gathering the user requirements and inputs for the on-board HMI (Human Machine Interface) and the other part considering the prioritisation of previous scenarios and the possibility to propose new accident situations. In the last section the use cases analysis completing the deliverable is carried out. The main outcome of the deliverable is the selection of eight relevant use cases that are prioritised via their estimated relevance for road safety. These use cases have been parameterised to enable the subsequent definition of system functionality and specifications. The key parameters, identified by experts and evaluated by users by means of an on-line questionnaire, are: type of vehicle and of vulnerable road user, type of road, relative trajectories, vehicle’s and vulnerable users’ speed, time to collision, time of the day, weather. Finally each use case has been commented by experts that included a very preliminary evaluation of their technological feasibility within the WATCH-OVER framework.




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2. Preliminary information The objectives of this activity are first of all to define the needs and requirements of different road users regarding a prevention system to avoid accidents which involve vulnerable road users (VRU) and secondly to identify the most critical scenarios of use and describe the related use cases for the WATCH-OVER system. As vulnerable road users are identified pedestrians, bicyclists and drivers of powered two-wheelers. The study described in the first section is based on the results of previous related projects, regarding user requirements, scenarios and use cases and also accident analysis. Their consideration leads to a better understanding of the problem to be solved as well as to a part of the specifications of the WATCH-OVER scenarios and use cases. In the second part a review of previous accident surveys is performed accompanied by a statistical analysis, in order to identify the pre-crash scenarios (accident configurations) most relevant to VRU and the parameters that should be considered by WATCH-OVER framework. In this section only the statistical data and major results is presented. The third part complements the initial list of scenarios depicted from accident investigation with dedicated expert brainstorming sessions.

2.1. Previous related projects Previous projects are an important input for the WATCH-OVER framework because they are a heading contribution for starting the implementation of the system architecture. Of course it is not possible to rely on the requirements evaluated in previous (and not up-to-date) tasks, but the experiences gathered especially from PROTECTOR and SAVE-U projects for user needs and from MAIDS project for scenarios and use cases will be really important for a proper project activity fulfilment.

2.1.1. The PROTECTOR European project

PROTECTOR was an EU co-funded project (IST–1999–10107) for the protection of pedestrians. The objective of the project was to develop an active safety system for vulnerable road users based on different sensor technologies. This project performed an extensive user needs survey. After focus groups and discussions with accident experts and road users, the project defined five basic scenarios and selected a set of several parameters for each scenario (day-time, number of targets, type of vulnerable road user etc.). This resulted in 14 scenarios being presented to the public via a multimedia questionnaire. The aim of this survey was to gather users’ opinion on the comparative risk of each scenario, on the sustainability of the situation, on the level of support needed per scenario and on the users’ willingness to pay for a relevant system. 196 users from Germany and 180 from Italy completed this survey. The questionnaire has been considered within this report for the identification of the most relevant scenarios as judged from the respondents. The relevant conclusions emerging in the study were that users considered as the most dangerous accident configurations those where a pedestrian is crossing perpendicularly a road occluded from parked cars, while the vehicle is approaching and the risk increases while the distance becomes closer. Other inputs were that night enhances the risk factor, when compared to day and multiple pedestrians are more dangerous than one pedestrian. These results have been considered within Paragraph 2.3.1.

2.1.2. The SAVE-U European project

SAVE-U was an EU co-funded project (IST–2001–34040) focused on avoiding accidents that involve vulnerable road users. The objective was to develop sensors and system architecture for




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vulnerable users’ protection, with major focus on pedestrians and bicyclists. Initially, this project performed an analysis of the characteristics of VRU accidents, using accident data from Europe, the USA and Japan up to 2001. In summary the conclusions are:

• Pedestrians are the second largest category involved in traffic accidents worldwide, after vehicle occupants, while bicyclists and motorcyclists are in third place.

• Passenger cars are the collision opponents in the large majority of pedestrian accidents in Europe. For bicyclists, the passenger car group is less represented in accidents and a sizeable portion of accidents involves (light) trucks as collision opponent.

• The large majority of pedestrian accidents occur at collision speeds below 50 km/h. The vehicle speed interval, where most improvement could be achieved with respect to pedestrian injury level, is 30-50 km/h. Collision speeds involving bicyclists are somewhat higher.

• A large majority of pedestrian accidents happens during daytime conditions (according to studies mainly done in France and Germany). A significant minority of fatal accidents however occurs at night. Aggregated data from Europe and the US appear to paint different pictures regarding the influence of lighting conditions.

• A large majority of non-motorist accidents occurs during normal (dry) weather conditions.

• The vast majority of pedestrian accidents occurs in an urban area. For fatal pedestrian accidents, the rural area increases in relevance.

• Intersections account for a minority of the pedestrian and bicyclists accidents.

• The large majority of pedestrian and bicyclist accidents involves a vehicle going approximately straight ahead on the road (i.e. no turns at intersection or backing out).

The findings have been reviewed and the statistical data contained within the SAVE-U reports have been considered in the present deliverable, in the section regarding accidents involving pedestrians and bicyclists (paragraph 2.2.2 and 2.2.3).

2.1.3. The MAIDS European project

MAIDS was a research project led by the Association of European Motorcycle Manufacturers (ACEM) with the support of the European Commission. The project aim was to perform a European study on powered two-wheelers (PTW, represented by motorbikes and mopeds) accidents. The MAIDS partners included the European Commission, AMA (American Motorcyclist Association), FIM (Federation Internationale de Motocyclisme), FEMA (Federation of European Motorcyclists Association), BMF (British Motorcyclists Federation), while a lot of PTW manufacturers participated in the Management Group of the project. MAIDS selected five regions in five countries (France, Germany, Italy, the Netherlands and Spain) as an adequate sample of the PTW population in Europe. The collection of data and statistical analysis was performed by five independent research institutes among the five countries. MAIDS was an epidemiological study, therefore two groups of cases were collected, 921 cases (accidents) and 923 controls. The aggregate MAIDS database consists of a total of 921 in-depth accident investigations during the period 1999-2000 and includes approximately 2000 variables for each accident, which enabled the identification of all human, environmental and vehicle factors which may have contributed to the outcome of the accident. Besides, data was collected by further 923 cases of riders and PTWs in the same areas that were not involved in accidents, to provide exposure information. The MAIDS final report provides detailed analysis of this database as far as accident causation, vehicles, environmental factors, human factors and systems for driver protection are concerned. This has been reviewed and used in the present deliverable, in the section regarding accidents of PTW. The aggregated data are considered into this document within the accident survey as relevant data source.




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2.2. Review of accident data In this section various accidents statistics are presented separately per VRU category, i.e. pedestrians, bicyclists and powered two-wheelers riders. Several databases have been queried so as to identify the circumstances under which the accidents with the involvement of VRUs are more frequent. Besides analysis of databases, the results of previous accident analyses are taken into account, especially where they refer to in-depth studies, since in-depth databases are in general not publicly available. The survey considers data coming from related projects accident analysis, EU countries statistical information and relevant studies in this field. Statistical figures of EU countries come from EUROSTAT (EU-15 and EU-25), CARE (Community Road Accident Database), ECMT (European Conference of Ministers of Transport), ETSC (European Transport Safety Council), BAST (Bundesanstalt für Straßenwesen, Germany), SWOV (Stichting Wetenschappelijk Onderzoek Verkeersveiligheid, the Netherlands), ISTAT (Istituto Centrale di Statistica, Italy). The inputs have been analysed extensively with the objective to collect all important information that allow an understanding on how accidents (that involve VRU) happen and how it is possible to characterise them. The major outcome should be a group of typical or most common accident configurations useful to determine critical scenarios and a set of possible parameters that should be used to compute and measure the accident dynamic to identify the use cases. Numerical data extracted from database analysis could not alone be exhaustive for all information needed in accident survey, but they represent a first basis where to start the pre-crash and crash conditions study. The EU available statistical data are integrated where possible with two key USA traffic databases, General Estimates System (GES) and Fatality Analysis Reporting System (FARS). These databases give an important contribution in the accident survey regarding especially urban and sub-urban areas, where scenarios are more likely to be similar to the European ones, differently from highways environment where many differences could be underlined. GES is a probability-based nationally representative sample of all police-reported fatal, injury, and property damage crashes. The data from GES yield USA national estimates, calculated using a weighting procedure, but cannot give State-level estimates. Also GES is a sample of motor vehicle crashes and the results generated are estimates. FARS is a census of crashes involving any motor vehicle on a traffic way, but only fatal crashes. It is generally considered to be the most reliable USA national crash database. Several variables are examined in details throughout next paragraphs, providing specific results and observations. A description is given in Table 1.

N. PARAMETER DESCRIPTION 1 Accident configuration The first aspect considered is the accident configuration. It gives an

immediate overview of the situation where the accident happened. From this variable it is possible to gather the percentages of accidents that occurred with similar geometric characteristics.

2 Collision opponent It tells about the main actors involved in an accident. 3 Collision speed Collision speed is the recognised velocity registered before the impact.

It can be represented with an absolute speed (one moving opponent and a static one) or a relative velocity (both the opponents moving). Even if the WATCH-OVER target speed is 50 km/h, this aspect is important to discover the velocities at which the accident occurs more often.

4 Time of day It gives the percentages of when an accident between a vehicle and a VRU happens. It is possible to gather when the fatalities or injuries occur more often, and the most proper scenario lighting.




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N. PARAMETER DESCRIPTION 5 Road conditions Road condition is referred to the road surface status at the time of the

incident. It is partially related to the weather conditions, as for example the rain makes the road more slippery. The percentages of most commonly occurring road conditions should be used for scenarios’ prioritisation.

6 Accident location It highlights where the accident happened. It is an important input to distinguish events occurred in an urban area or on a rural/sub-urban road.

7 First contact point Whenever an accident occurs the first contact point tells about the visibility of the collision opponent at the time of the event. From this information it is possible to understand if the VRU should have been visible by the camera sensor and how much the communication technology can help to increase the recognition of the VRU.

8 Age group of user It indicates the percentages of accidents occurred to different road users, dividing them in different age groups. This variable gives an idea about the typology of people involved in the event, and so it is possible to derive the range of speeds of the pedestrians mostly related to road accidents.

Table 1: Parameters considered in accident statistical survey

2.2.1. Problem size

As a first consideration, the importance of the WATCH-OVER research and development emerges immediately at first look to the data regarding European road accidents. It is a fact that still the number of accidents on European roads is unacceptably high, and among the victims involved a very relevant percentage is related to pedestrians, bicyclists and motorcyclists. In Figure 1 and Figure 2 absolute and relative figures of road accidents (injured and killed people) are presented respectively.

Figure 1: Road injuries and fatalities (CARE, EU-15 2002)




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Figure 2: Road fatalities per one thousand of population in EU-25 (BAST 2003)

According to the CARE and ETSC data and to the SAFETYNET project Deliverable n. 1, among all fatalities around 40% concern vulnerable road users (pedestrians, bicyclists or PTWs).

(1) Significant variations in the reporting method are observed among different Member States. (2) Including mopeds.

Table 2: Total number of fatalities per country (CARE, EU-15 2002)




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From the previous table, pedestrians are accounted for 14.9% of fatalities, bicyclists accounted for 5.2% of fatalities, drivers and passengers of powered two-wheelers (motorcycles and mopeds) accounted for 17% of all fatalities (data from 2002 for EU-15).

Figure 3: Fatalities in 2002 in 14 EU countries (SAFETYNET Del. 1)

Data from 2002 for EU-14 countries account pedestrians for 15.1% of fatalities, bicyclists for 4.7%, drivers and passengers of powered two-wheelers (motorcycles and mopeds) for 17.4%. Previous figures are in line with data on road fatalities derived from the German national statistics in the years 2002-2004, as shown below.

2002 2003 2004

PEDESTRIANS 12.76% 12.28% 14.34%

BICYCLISTS 8.52% 9.31% 8.13%

POWERED TWO-WHEELERS 15.26% 16.33% 16.78%

TOTAL INVOLVING VRU 36.54% 37.92% 39.25%

Table 3: VRUs fatalities based on German national data (2002-2004)

2.2.2. Pedestrians

In this paragraph a summary of the outcomes elaborated from different data base investigations on accidents with pedestrians is presented. Accident configuration An analysis of 1337 pedestrian-vehicle accidents, derived from the extended GIDAS (Grafisch-Interaktives Datenanalysesystem) database, is included in Stanzel 2002. According to this analysis, 46.64% of pedestrian accidents involve the vehicle going straight and the pedestrian entering the road, either occluded or not occluded from the left or right side, the vehicle not being at junction.




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Figure 4: Pedestrian-Vehicle accident configurations (Stanzel 2002)

In addition, according to FARS 2004 USA data, in 78.54% of fatal accidents involving pedestrians the other vehicle was going straight. According to GES 2004 USA data, in 62.93% of accidents involving pedestrians the other vehicle was going straight, in 13.81% the other vehicle was turning left and in 7.17% of cases it was turning right.

VEHICLE MANOEUVRE PERCENTAGE OF FATAL

ACCIDENTS (FARS 2004) PERCENTAGE OF ALL

ACCIDENTS (GES 2004) Going Straight 78.54% 62.93% Slowing or Stopping in Traffic Lane 0.56% 1.25% Starting in Traffic Lane 0.47% 1.71% Stopped in Traffic Lane 4.78% 0.16% Passing or Overtaking Another Vehicle 0.93% 1.19% Leaving a Parked Position 0.10% 0.78% Parked 0.19% 0.05% Entering a Parked Position 0.10% 0.42% Turning Right: Right Turn On Red Permitted 0.29% Turning Right: Right Turn On Red Not Applicable or Not Known if Permitted

1.20% 7.17%

Turning Left 3.71% 13.81%




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ACCIDENTS (GES 2004) Making a U-Turn 0.03% 0.26% Baking up (not parking) 1.22% 2.80% Changing Lanes or Merging 1.78% 1.30% Negotiating a Curve 1.90% 1.51% Other / Unknown 4.19% 4.66%

Total 100.00% 100.00%

Table 4: Vehicle manoeuvre in accidents with pedestrian involvement (FARS, GES from USA)

Collision opponent The most common collision opponents for pedestrians are passenger cars. Indeed 74% of pedestrian fatalities in 2000 in Germany are related to passenger cars as collision opponent (BAST 2000). The same findings are supported by FARS and GES 2004 USA data, as shown below.

PASSENGER CAR VAN TYPE PICKUP LIGHT TRUCK BUS TRUCK MOTORCYCLE OTHER TOTAL

43.88% 22.35% 17.41% 0.02% 1.44% 6.85% 0.78% 7.27% 100.00%

Table 5: Fatal accidents involving pedestrians per body type of other vehicle (FARS)

AUTOMOBILES UTILITY VAN-LIGHT TRUCK BUS TRUCK MOTORCYCLE OTHER TOTAL

56.18% 10.23% 23.88% 1.09% 3.79% 0.62% 4.21% 100.00%

Table 6: Accidents involving pedestrians per body type of other vehicle (GES)

Collision speed The survey within the project SAVE-U reveals that in 2001 85% of all pedestrian accidents in four world regions (the USA, Japan, Europe and Australia) involve an impact velocity of 50 km/h or smaller. Also the entries from 2004 FARS USA database are presented below (in the next figure collision speed in km/h is on x-axis and fatal accidents percentage is on y). The majority of fatal accidents with pedestrian involvement is in the area 50-90 km/h. Within this range 25.3% of occurrences happens, while below 50 km/h the percentage is 12%. In 59.12% the speed of the vehicle is not known.

Fatal accidents with pedestrian involvement

0%

2%

4%

6%

8%

10%

0 10 20 30 40 50 60 70 80 90 100 110 120 130 >130

Vehicle speed in km/h

Pe

rce

nta

ge

of

fata

l

ac

cid

en

ts

Figure 5: Collision speed (when known) in fatal accidents with pedestrians (FARS 2004)




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According to GES 2004 USA data, 18.02% of accidents involving pedestrians occur in the area from 1 to 50 km/h, however in 73.16% of accidents the speed of the vehicle is not known. Time of day According to the SAFETYNET project there is a peak of pedestrian fatalities in the time of 17-21, which can be detected both in the 1993 and 2002 data.

Figure 6: Number of pedestrian fatalities by hour of day, EU-14 2002

The same peak is depicted in 2003 data from SWOV, the Dutch research institute for road safety, which are available through the Scientific Statistical Agency (CBS) and the Dutch Ministry of Transport (AVV), as shown below.

0

10

20

30

40

50

60

70

80

90

100

1.00

h

3.00

h

5.00

h

7.00

h

9.00

h

11.0

0h

13.0

0h

15.0

0h

17.0

0h

19.0

0h

21.0

0h

23.0

0h

Dead

Hospital

1st aid

injured

Figure 7: Number of pedestrian fatalities and injuries by hour of day (SWOV data 2003)




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According to FARS 2004 USA data the majority of fatal accidents involving pedestrians occurs at darkness, while the majority of all accidents is during daylight, as shown below.

ACCIDENT TYPE DAYLIGHT DARK DARK BUT LIGHTED DAWN DUSK OTHER / UNKNOWN

FATAL ACCIDENTS (FARS 2004) 29.49% 32.45% 33.72% 1.61% 1.84% 0.89%

ALL ACCIDENTS (GES 2004) 58.15% 9.45% 27.52% 1.40% 2.80% 0.67%

Table 7: Accidents involving pedestrians in the US per lighting condition (FARS, GES)

Road conditions As EU databases are not giving clear indications on the correlation of road accidents involving VRU with road conditions, the USA data are considered. According to FARS and GES 2004 data, the majority of accidents and fatal accidents with pedestrian involvement took place on dry road.

ACCIDENT TYPE DRY WET ICY, SNOWY OR SLUSHY OTHER / UNKNOWN

FATAL ACCIDENTS (FARS_TBD 2004) 83.52% 13.37% 1.84% 1.27%

ALL ACCIDENTS (GES 2004) 80.89% 15.52% 2.08% 1.51%

Table 8: Accidents involving pedestrians in the USA per road condition (FARS, GES)

From the USA data it is not possible to find the reason, but it could simply be that drivers move more carefully and pay greater attention when there is a slippery road and there are fewer people walking when it is raining. Accident location According to the SAFETYNET project based on 2002 data from 14 EU countries:

• 65.3% of pedestrian fatalities happened inside urban areas.

• 50.12% of pedestrian fatalities occurred in locations other than junctions.

• 31.44% of pedestrian fatalities occurred in T or Y junctions.

• 9.77% of pedestrian fatalities occurred in crossroads. These findings are also supported by FARS 2004 USA data, as shown below.

PERSON TYPE HIGHWAY RURAL URBAN OTHER / UNKNOWN

PEDESTRIAN 15.38% 24.23% 59.52% 0.87%

Table 9: Location of fatal accidents with pedestrian involvement (FARS)

Moreover according to FARS 2004 USA data:

• 70.51% of fatal accidents involving pedestrians occurred in locations other than junctions.

• 15.29% of fatal accidents involving pedestrians occurred in intersections.

• Another 9.17% of such accidents were intersection related. According to GES 2004 USA data:

• 45.38% of accidents involving pedestrians occurred in locations other than junctions.

• 20.82% of accidents involving pedestrians occurred in intersections.

• Another 26.74% of such accidents were intersection related. First contact point The first contact point to a vehicle regarding pedestrian accidents is given below, according to the SAVE-U project. 67% of accidents involve the frontal side of the vehicle.




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Figure 8: First contact point for vehicle-pedestrian accidents (SAVE-U Del. 1A)

This is further supported by GES 2004 data, where in 67.51% of accidents with pedestrians the impact area on the vehicle is the frontal one.

IMPACT AREA ON VEHICLE PERCENTAGE OF ACCIDENTS Front 60.96% Front right corner 3.95% Front left corner 2.60% Right side 13.08% Left side 8.31% Back 3.69% Back right corner 0.31% Back left corner 0.16%

Table 10: Impact area on other vehicle for vehicle-pedestrian accidents (GES)

Age group According to the SAFETYNET project (2002 data from 14 EU countries):

• 43.9% of pedestrian fatalities befall the age group 65+ years old.

• Another 38.9% of pedestrian fatalities befall the age group 25-64 years old. Relevant 2004 data from USA state that:

• 58.64% of pedestrian fatalities and 45.59% of pedestrian injuries befall the age group 25-64 years old.




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• 20.14% of pedestrian fatalities and 45.59% of pedestrian injuries befall the age group < 24 years old.

• 21.22% of pedestrian fatalities and 8.82% of pedestrian injuries befall the age group > 65 years old.

All the age groups shall be considered, but it is relevant to see previous figures because the different groups have differences in walking speed, reaction characteristics, etc..

2.2.3. Bicyclists

In this paragraph there is a summary of the data found in different databases, regarding accident involving bicyclists. Accident configuration According to the SAFETYNET project in 2002 in 14 EU countries 39.35% of pedal cyclist fatalities were related to lateral collision with another vehicle and 17.98% with chain or rear collision with another vehicle. The percentages are presented below.

animal; 0.00% chain or rear;

17.98%

frontal; 7.47%

lateral; 39.35%

other; 10.44%

parked vehicle;

0.14%

single vehicle;

8.16%

not defined;

16.46%

Figure 9: Collision types according to SAFETYNET Del. 1

According to FARS 2004 USA data, in 82.47% of fatal accidents involving bicyclists the other vehicle was going straight. According to GES USA 2004 data, in 48.46% of accidents involving bicyclists the other vehicle was going straight, in 22.02% it was turning right and in 14.68% it was turning left.



ACCIDENTS (GES 2004) Going Straight 82.47% 48.46% Slowing or Stopping in Traffic Lane 0.76% 1.10% Starting in Traffic Lane 1.02% 3.87% Stopped in Traffic Lane 0.51% 2.60% Passing or Overtaking Another Vehicle 2.29% 0.63% Turning Right: Right Turn On Red Permitted

1.02%

Turning Right: Right Turn On Red Not Applicable or Not Known if Permitted

3.05% 22.02%

Turning Left 2.67% 14.68% Making a U-Turn 0.25% 0.47% Baking up (not parking) 0.25% 0.39% Changing Lanes or Merging 1.14% 0.39%




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ACCIDENTS (GES 2004) Negotiating a Curve 2.16% 1.50% Other / Unknown 2.41% 3.89%

Total 100.00% 100.00%

Table 11: Vehicle manoeuvre in accidents with bicyclist involvement (FARS, GES)

Collision opponent 43% of bicyclists fatalities in 2000 in Germany were related to passenger cars as collision opponent (BAST 2000). Similar data are given by FARS 2004 and GES 2004 data, as shown below.

PASSENGER VAN TYPE PICKUP LIGHT TRUCK BUS TRUCK MOTORCYCLE OTHER TOTAL

39.90% 22.74% 20.20% 0.13% 0.76% 10.17% 1.02% 5.08% 100.00%

Table 12: Fatal accidents involving bicyclists per body type of other vehicle (FARS)

AUTOMOBILES UTILITY VAN-LIGHT TRUCK BUS TRUCK MOTORCYCLE OTHER TOTAL

59.75% 13.50% 20.60% 0.63% 2.29% 0.79% 2.45% 100.00%

Table 13: Accidents involving bicyclists per body type of other vehicle (GES)

From FARS data it emerges that 82.84% of all fatalities regards an occurrence between a bicycle and a car or similar vehicle (van or pick-up); just 1.02% is representative of incidents between a bicycle and a motorcycle. Similar figures come out from GES database. Collision speed The survey within the SAVE-U project reveals that 48.9% of bicyclists’ accidents occurred in the initial vehicle speed range of 50-80 km/h. Data from the FARS database (2004) are presented below. The majority of fatal accidents with bicyclist involvement is in the area 40-90 km/h. Within this range 36.98% of occurrences happen, while below 50 km/h the percentage is 12.4%. In 54.38% the speed of the vehicle is not known.

Fatal accidents with bicyclists involvement

0%

2%

4%

6%

8%

10%

12%

0 10 20 30 40 50 60 70 80 90 100 110 120 130 >130

Vehicle speed in km/h

Pe

rce

nta

ge

of

fata

l

ac

cid

en

ts

Figure 10: Collision speed (when known) in fatal accidents with bicyclists involvement (FARS)

According to GES 2004 data, 28.73% of accidents involving bicyclists occurred in the area 1-50 km/h, however in 64.09% of accidents the speed of the vehicle is not known.




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Time of day As data available from EU databases are not giving relevant indications, the USA data are presented. According to FARS and GES 2004 the majority of fatal accidents or incidents involving bicyclists occur at daylight.




Table 14: Accidents involving bicyclists in the US per lighting condition (FARS, GES)

Road conditions Also in this case, as data available from EU databases are not giving relevant indications, the USA data are presented. According to FARS 2004 and GES 2004 data, the majority of accidents and fatal accidents with bicyclist involvement took place on dry road.

ACCIDENT TYPE DRY WET ICY, SNOWY OR SLUSHY OTHER / UNKNOWN

FATAL ACCIDENTS (FARS 2004) 89.82% 9.22% 0.28% 0.69%


Table 15: Accidents involving bicyclists in the US per road condition (FARS, GES)

As for pedestrians, previous figures could bring to the observation that most of bicycling is done with no rain. Another possible reason could be that drivers move more carefully and pay greater attention when there is a slippery road. Accident location According to the SAFETYNET project, in 2002 in 14 EU countries 49.6% of pedal cyclists fatalities occurred inside urban areas, while 50.4% occurred outside urban areas. According to 2004 German national data, 89.42% of bicyclists injuries and 56.42% of bicyclists fatalities occurred inside urban areas. These findings are also supported by FARS data 2004, as shown below.

PERSON TYPE HIGHWAY RURAL URBAN OTHER / UNKNOWN

BICYCLIST 3.03% 33.15% 63.00% 0.83%

Table 16: Location of fatal accidents with bicyclist involvement (FARS)

Furthermore, according to FARS 2004 data:

• 57.01% of fatal accidents involving bicyclists occurred in locations other than junctions.

• 66% of bicyclists fatalities occurred in urban areas and 67% at non-intersection locations.

• 29.03% occurred in intersections.

• Another 6.74% were intersection related. According to GES 2004 data:

• 19.57% of accidents involving bicyclists occurred in locations other than junctions.

• 43.65% of accidents involving bicyclists occurred in intersections.

• Another 18.86% of such accidents were intersection related.

• 16.18% of such accidents occurred in driveway-alley access. First contact point The first contact point for cyclist accidents is given below, according to the SAVE-U project. In 82.8% of all accidents the first contact point is in front of the vehicle.




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Figure 11: First contact point for vehicle-bicyclists accidents (SAVE-U Del. 1A)

According to GES 2004 data, in 63.78% of accidents with bicyclists the impact area on the other vehicle was the frontal one.

IMPACT AREA ON OTHER VEHICLE PERCENTAGE OF

ACCIDENTS Front 55.88% Front right corner 4.66% Front left corner 3.24% Right side 22.97% Left side 8.05% Back 1.18% Back right corner 0.32% Back left corner 0.08%

Table 17: Impact area on other vehicle for vehicle-bicyclists accidents (GES)

The finding seems not in agreement with the first paragraph of this section, Accident configuration, where it is said “According to SAFETYNET project in 2002 in 14 EU countries 39.35% of pedal cyclist fatalities are related to lateral collision”. The justification is found in the fact that the SAFETYNET project considers the bicyclist fatalities, while in this paragraph all vehicles/bicyclist incidents are considered. Age group According to SAFETYNET project based on 2002 data from 14 EU countries:

• 43% of pedal cyclists fatalities befall the age group 25-64 years old.

• 37.8% of pedal cyclists fatalities befall the age group 65+ years old. According to German national data in 2004, the age groups of bicyclists injured or killed in accidents are given below. All age groups are more or less equally distributed in injuries, but the majority of fatalities is in the group 65+ years old.




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AGE GROUP < 15 15-18 18-25 26-35 35-45 45-55 55-65 > 65

INJURIES 17.98% 8.15% 10.17% 12.21% 15.71% 12.31% 10.61% 13.19%

FATALITIES 4.84% 3.16% 3.58% 3.37% 11.16% 11.37% 15.37% 47.16%

Table 18: Injuries and fatalities of bicyclists in Germany in 2004

According to FARS 2004 data, bicyclists younger than 16 accounted for 21% of all bicyclist fatalities and 32% of bicyclist injuries.

2.2.4. Powered two-wheelers

After pedestrian and bicyclist accident analysis, in this paragraph the most significant statistical data for PTWs are presented. For this VRU category it is important to highlight that, as indicated in the European regulation, PTWs can be divided into several different vehicle categories, based upon their engine capacity and design speed. There are currently two dominant PTW legal categories: the L1 and L3 vehicle categories. L1 vehicles include both mopeds and mofas while L3 vehicles include motorcycles. The definitions of these categories are as follows:

• Moped. A two wheeled vehicle with an engine cylinder capacity in the case of a thermic engine not exceeding 50 cm3 and whatever the means of propulsion a maximum design speed not exceeding 50 km/h. A moped is an L1 vehicle and might be designed to have pedals, or not to have pedals.

• Mofa. A moped with a maximum design speed not exceeding 25 km/h. A mofa is an L1 vehicle and might be designed to have pedals, or not to have pedals.

• Motorcycle. A two wheeled vehicle with an engine cylinder capacity in the case of a thermic engine exceeding 50 cm3 or whatever the means of propulsion a maximum design speed exceeding 50 km/h. A motorcycle is an L3 vehicle.

The MAIDS reports use the term PTW to describe all powered two-wheelers. Accident configuration According to SAFETYNET project 29.32% of moped and motorcycle fatalities are related to lateral collision with another vehicle, 15.43% with frontal collision with another vehicle, 7.87% a chain or rear collision with another vehicle. The results are presented in the figure below.

animal; 0.12%

chain or rear; 7.87%

frontal; 15.43%

lateral; 29.32%

other; 9.81%

parked vehicle;

0.61%

single vehicle;

24.01%

not defined; 12.84%

Figure 12: Collision types according to SAFETYNET Del.1




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According to MAIDS data, the ranking statistics about PTW accident configurations is given in the following figure, where there is the separation into the categories L1 and L3, as explained earlier. “OV” stands for Other Vehicle.

15

28

4

25

15

37

24

44

24

35

39

108

20

45

31

43

21

35

29

55

47

45

145

7 2,40%

5,20%

5,30%

6,10%

6,30%

6,30%

6,40%

7,90%

8,60%

8,90%

9,10%

27,30%

0 50 100 150 200 250 300

OV turning right in front of PTW, PTE perpendicular to

OV path

Head –on collision of PTW and other vehicle

PTW running off roadway, no OV involvement

PTW overtaking OV while OV turning left

PTW falling on roadway, no OV involvement

OV into PTW impact at intersection; paths perpendicular

PTW impacting rear of OV

Other PTW/OV impacts

PTW & OV traveling in opposite directions, OV turns in

front of PTW, PTW impacting OV

OV turning left in front of PTW, PTW perpendicular to OV

path

PTW into OV impact at intersection; paths perpendicular

Other (includes 13 different categories below 5%)

L3 vehicles

L1 vehicles

Figure 13: number of PTW accidents related to a particular configuration (MAIDS 2004)

The highest percentage is found in the event “PTW into other vehicle impact at intersection; paths perpendicular” with 9.10%, but it emerges that most relevant percentages are related to intersections area and perpendicular paths. MAIDS (2004) also found that:

• In 63.7% of accidents the PTWs were travelling in a straight line after the precipitating event.

• In 2.1% of accidents the PTWs were turning right.

• In 5.2% of accidents the PTWs were turning left.

• In 5.9% of accidents the PTWs were negotiating a bend at constant speed.

• In 6.1% of accidents the PTWs were performing a passing manoeuvre on the left.

• In 38.4% of accidents the OV was moving in a straight line.

• In 8.3% of accidents the OV was turning right.

• In 31.6% of accidents the OV was turning left.

• In 4% of accidents the OV was making a U-turn left. According to FARS 2004 data, in two vehicles fatal crashes with the involvement of a motorcycle, 78% of motorcycles were impacted in the front and only 6% were struck in the rear. From the same data source:

• In 39% of two vehicles fatal crashes with the involvement of a motorcycle, the other vehicle was turning left, while the motorcycle was going straight, passing or overtaking the vehicle.




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• In 26% of such accidents, both vehicles were going straight. According to GES 2004 data, in 62.23% of accidents involving PTW the PTW was going straight, in 8.55% it was passing/overtaking another vehicle, in 6.36% it was negotiating a curve.

PTW MANOEUVRE PERCENTAGE OF ALL ACCIDENTS (GES 2004) Going Straight 62.23% Slowing or Stopping in Traffic Lane 3.58% Starting in Traffic Lane 0.80% Stopped in Traffic Lane 3.98% Passing or Overtaking Another Vehicle 8.55% Turning Right 3.38% Turning Left 4.57% Making a U-Turn 0.40% Changing Lanes 5.17% Merging 0.20% Negotiating a Curve 6.36% Other/Unknown 0.78%

Total 100.00%

Table 19: PTW manoeuvre in accidents with PTW involvement (GES)

Collision opponent The table below presents the results of MAIDS project in-depth investigations of accidents opponents involving powered two-wheelers.

PTW COLLISION PARTNER PERCENTAGE Passenger car 60% Roadway 9.0% Truck / SUV 8.4% Fixed object 8.0% Another PTW 6.9% Parked vehicle 2.7% Other 2.5% Bicycle / pedestrian 2.1% Animal 0.3% Total 100.0%

Table 20: MAIDS results on PTW collision partner (MAIDS 2004)

According to GES 2004 data, the PTW collision opponent is a passenger car in 57.46% of the cases, as shown below.

PTW COLLISION PARTNER PERCENTAGE Passenger car 57.46% Light truck 10.34% Medium / heavy truck 8.75% Other 23.46% Total 100.0%

Table 21: PTW collision partner in accidents in US (GES 2004)

From the figures above, the accidents between a PTW and a bicyclists or pedestrian are minimal in MAIDS values (2.1%), while they are considered in the “other” category within the GES data.




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Collision speed MAIDS results indicate that:

• In 73.8% of accidents investigated there was no differential of speed between the PTW and the surrounding traffic.

• PTW speed difference with surrounding traffic, either below or above, contributed to accident in 18% of cases.

• In 85.6% of cases the Other Vehicle (OV) speed was not unusual.

• In 4.8% OV speed difference contributed to the accident.

• In 65.3% of non-single accidents the PTW speed was in the area 30-60 km/h.

• 73.8% of OVs were travelling at a speed below 40 km/h. GES 2004 entries indicate that:

• In 21.87% of accidents with PTW involvement the PTW speed was below 50 km/h.

• In 18.49% of accidents the PTW speed was from 51 to 120 km/h.

• However, in 55.07% of cases the PTW speed is not known. While considering the speeds of the opponents, there is a lack of complete information (see GES database, where in 55.07% PTW speed is not known). This aspect is more significant for PTW, because while for pedestrians and bicyclists their velocities are in most cases negligible compared to those of the vehicles, this is not true for motorbikes. Time of day MAIDS data (2004) indicate that most accidents occurred between 17 and 18, while most of the fatal accidents took place between 19 and 20. Regarding lighting, the following was found according to the same study:

CONDITION PERCENTAGE Daylight 73% Dusk/dawn 8.2% Night without street lighting 3.7% Night with street lighting 15.1%

Table 22: Illumination at time of accident (MAIDS 2004)

The results from the USA 2004 data are similar, as shown below.




Table 23: Light conditions in accidents with PTW involvement (FARS, GES)

Weather / road conditions MAIDS results (2004) indicate that:

• Weather is a contributing factor for the PTW in 7.4% of accidents and in 4.7% of accidents for the OV.

• The weather conditions are dry in 89.9% of cases, while rain is noted in 7.9% of all cases.

• Visibility limitation due to weather is noted in 3.1% of cases for the PTW and in 3.2% for the other vehicle.

• Regarding the PTW driver, stationary view obstructions (signs, buildings, etc.) are reported in 18.1% of all cases. Mobile view obstructions are in 9.5% of cases. Automobiles are mentioned in 6.0% of all cases, light trucks and vans in 2% and trucks and buses in 1%.

• Regarding the OV driver, stationary view obstructions (buildings, vegetation, parked vehicles, etc.) are reported in 20.5% of all cases. Mobile view obstructions are reported in




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11.6% of cases. Automobiles are mentioned in 6.8% of all cases, light trucks and vans in 2.2% and trucks and buses in 1.5%.

According to US 2004 data, the majority of accidents and fatal accidents with the involvement of PTW occurs at dry conditions.

ACCIDENT TYPE DRY WET SNOW, SLUSH OR ICE OTHER/ UNKNOWN

FATAL ACCIDENTS (FARS 2004) 95.71% 3.50% 0.03% 1.00%


Table 24: Road condition in accidents with bicyclists involvement in the US (FARS, GES)

Accident location According to SAFETYNET project, based on 2002 data from 14 EU countries:

• 55.1% of moped fatalities occurred inside urban areas, while 57.3% of motorcycle fatalities occurred outside urban areas.

• 51.3% of moped/motorcycle fatalities occurred while not being at junction.

• 29.8% of moped/motorcycle fatalities occurred while being at junction, most of them in t/y junction, followed by crossroad.

According to German national data in 2004, 67.88% of injuries and 24.69% of fatalities of occupants of powered two-wheelers occurred inside inhabited areas. 89.5% of accidents involving motorcyclists injuries occurred in urban areas in Germany in 1998 (BAST). According to MAIDS results (2004):

• 72.3% of accidents involving PTW occurred in urban areas.

• 54.3% of accidents occurred at an intersection. The same conclusions derive from the FARS 2004 data as shown below.

VEHICLE TYPE HIGHWAY RURAL URBAN OTHER / UNKNOWN

POWERED 2-WHEELERS 10.76% 47.05% 41.63% 0.56%

Table 25: Traffic environment of fatal accidents with motorcycle involvement (FARS)

According to the same data source:

• 62.13% of fatal accidents involving PTW occurred at non-junctions.

• 24.41% of such accidents occurred at intersections. According to GES 2004 data:

• 35.59% of accidents involving PTW occurred at non-junctions.

• 25.84% of such accidents occurred at intersections and 17.89% were intersection-related.

• 15.11% of such accidents occurred at driveway-alley access. First contact point The lines of sight between PTW and other vehicles are presented below (MAIDS 2004). 89.6% of other vehicles (OV) are in front of the PTW rider at the time of the precipitating event. In 60% of cases the PTW appears in front of the OV at the time of the precipitating event.




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Figure 14: PTW line of sight to Other Vehicle (MAIDS 2004)

Figure 15: Other Vehicle line of sight to PTW (MAIDS 2004)




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According to GES 2004 data, in 55.87% of accidents with PTW the impact area on the other vehicle was the frontal one, while in 17.69% it was the left side.

IMPACT AREA ON OTHER VEHICLE PERCENTAGE OF ACCIDENTS Front 53.48% Front right corner 1.79% Front left corner 0.60% Right side 9.94% Left side 17.69% Back 6.96% Back right corner 0.40% Back left corner 0.00%

Table 26: Impact area on other vehicle for accidents involving PTW (GES)

Age group According to SAFETYNET project:

• 59.5% of moped and motorcycle drivers fatalities and 41% of passengers fatalities befall the age group 25-64 years old.

• 29.1% of moped and motorcycle drivers fatalities and 41.5% of passengers fatalities befall the age group 16-24 years old.

MAIDS (2004) results reveal that 36% of PTW drivers are 26-40 years old. According to German national data (2004), the age groups of occupants of powered two-wheelers injured or killed in accidents are given below. 24.48% of injuries befalls the group 15-18 years old. 25.47% of fatalities befalls the group 35-45 years old.

AGE GROUP < 15 15-18 18-25 26-35 35-45 45-55 55-65 > 65

INJURIES 1.20% 24.48% 16.31% 15.24% 20.89% 12.69% 5.55% 3.63%

FATALITIES 0.41% 9.49% 16.84% 21.33% 25.47% 15.20% 6.22% 5.10%

Table 27: Injuries and fatalities of occupants of powered two-wheelers in Germany in 2004

2.3. Initial list of scenarios At this point it is possible to draw a first set of conclusions from the previous benchmark analysis. Based on the results from related projects and especially on the accident survey of paragraph 2.2, a pre-selection of scenarios considered as the most relevant in terms of expected safety impact is here reported. As previously, the different parts are divided depending on the VRU involved and they report:

• the main inputs from pedestrian, bicycles and motorbikes analysis;

• a summarising table with the key outcomes and the major parameters that should be considered for use case identification and prioritisation;

• a final table with scenario’s choice motivation and a simplified design.

2.3.1. Pedestrians

According to the statistical results, the WATCH-OVER system should cover all cases where there is a frequency of accidents occurrence (fatal or not) involving pedestrians. The highest percentage of accidents against pedestrian happens when the vehicle is going straight and the pedestrian enters the road, either occluded or not occluded from the left or the right side or when the vehicle is turning left and the pedestrian is entering the road, either occluded or not occluded. As a consequence in most of the occurrences the pedestrian is in front of the vehicle. Also circumstances where the pedestrian approaches the vehicle from the right or the left side (in




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respect to the vehicle direction) are notable. It is important to observe that the passenger cars should be selected as most relevant collision opponents in the WATCH-OVER scenarios, as the collision rate between pedestrian against bicyclists or motorbikes are limited from a statistical point of view. It is not straightforward to draw a precise remark about vehicle speed. Even if, referring to GES data, the highest percentage among known velocities in which an accident occurs is in the range of the vehicle target speed (up to 50 km/h) for the WATCH-OVER project, a potential conclusion is that system development should also consider collision mitigation as a mean to prevent injuries to VRUs. This is the reason why collision speed should be considered as a parameter. Scenarios should consider both night, as the majority of fatal accidents occur at night, but also day, as there is a peak of such accidents in the afternoon. Also the condition of day turning into evening should be taken into account. Because of this large set of inputs, the time of the day should be considered as a parameter. The highest percentage of accident happens on dry road. The urban environment represents the most important selection for WATCH-OVER pedestrian scenarios, but considering that occurrences may happen in a straight lane or in a crossroad one, also accident location should be taken as a parameter. All the major outcomes for each variable are summarised into the next table.

N. CONSIDERED

PARAMETER SUMMARY OF ACHIEVEMENTS NOTE

1 Accident configuration

1. Vehicle going straight and the pedestrian entering the road, either occluded or not occluded from the left or the right side.

2. Vehicle turning left and the pedestrian entering the road, either occluded or not occluded.

2 Collision opponent

Passenger cars (most relevant collision opponent).

3 Collision speed Different options. To be considered as a parameter

4 Time of day Day and night. Attention to dusk conditions. To be considered as a parameter

5 Road conditions

Dry road.

6 Accident location

Urban environment. To be considered as a parameter

7 First contact point

In front of the vehicle, right or left side.

8 Age group of user

All ages. To be considered as a parameter

Table 28: Pedestrian accident survey outcomes

Thus the following scenarios have been selected and sketched, as they account for 49.66% of accidents in Stanzel 2002. As additional information, the following configurations cover also at least 82.25% of the fatal accidents in the USA (FARS 2004). In this case the FARS information is considered important, because pedestrian accidents happened in urban environments (the largest percentage) could be considered similar in the USA and the EU. A motivation for each table item presented is given.




31

N. DESCRIPTION SKETCH

REASONING FOR

SELECTING THESE

SCENARIOS

1 Pedestrian crossing the road from the right to the left.

2

Pedestrian crossing the road from the right to the left occluded from a parked car.

The generic scenario, to which these two cases belong, represents one of the most frequent (30.78%) cases in the (Stanzel 2002) survey. This is also supported from PROTECTOR user needs survey that considered situation n. 2, with short distance between car and pedestrian, as the most critical scenario.

3 Pedestrian crossing the road from the left to the right.

This scenario is the second most frequent in the (Stanzel 2002) survey (frequency for the generic scenario is 15.86%).

4

Pedestrian crossing the road from the left to the right occluded from a parked car.

This scenario is the fourth most frequent in the (Stanzel 2002) survey (frequency for the generic scenario is 6.25%).

5

Vehicle turning left at an intersection, pedestrian crossing the road from the right to the left

6

Vehicle turning left at an intersection, pedestrian crossing the road from the right to the left occluded

These scenarios were selected as they are related to intersection. The frequency of the generic scenario in the (Stanzel 2002) survey is 3.26%.

Table 29: Proposed WATCH-OVER pedestrian-related scenarios




32

From Table 29 it can be observed that scenario n. 3 is covered by scenario n. 1 (one way road of n. 3 is symmetrical or better mirror-like in respect to the situation n. 1), so these two configurations will be considered as equal.

2.3.2. Bicyclists

In most accidents with bicyclist involvement the vehicle is going straight and there is a lateral collision of the bicyclist with the other vehicle. The WATCH-OVER scenarios related to bicyclists should include the passenger cars as collision opponents. In large part of all accidents the first contact point is in frontal/lateral part of the vehicle. Also for the bicyclists, as already seen for the pedestrians, the collision speed examination doesn’t bring to an immediate conclusion, especially because there is a lack of indication about the precise velocity of the different actors involved in the event. A first conclusion is that the system development should also consider collision mitigation as a mean to prevent injuries to VRU. A second conclusion is that the collision speed should be taken into account as a parameter variable for the research of the use cases. Daytime and dry road should be primarily considered for the WATCH-OVER system, covering the highest percentage of accidents. Urban environment appears as the most important for WATCH-OVER scenarios. While most of the fatalities occurs at non-intersection locations, the greatest percentage of all accidents happens near intersections. For this reason the accident location is chosen as a parameter. Also for this category of VRU all age groups shall be considered, but it is important to highlight the figure of fatalities in the range of 65+ years old, since this group is highly present and they have special characteristics of speed and reaction time. The outcomes on bicyclists’ accident analysis are summarised into Table 30.

N. CONSIDERED


1 Accident configuration

Lateral collision of the bicyclist with the other vehicle.


Passenger cars.

3 Collision speed Different options. To be considered as a parameter

4 Time of day Daylight (primary option). 5 Road

conditions Dry road.

6 Accident location

Urban environment (intersections and straight road). To be considered as a parameter


In front of the vehicle or on the right side.

8 Age group of user


Table 30: Bicyclist accident survey outcomes

In 39.35% bicyclist fatalities are related to lateral collision with another vehicle. According to FARS 2004 data, in 82.47% of fatal accidents involving bicyclists the other vehicle is going straight. Therefore the following scenarios have been selected.




33


REASONING FOR

SELECTING THESE

SCENARIOS

7

Vehicle on a crossroad, pedal cyclist crossing the road from the right.

8

Vehicle on a crossroad, pedal cyclist crossing the road from the left.

According to SAFETYNET Deliverable N. 1, 39.35% of bicyclist fatalities are related to lateral collision with another vehicle. According to FARS 2004 data, in 82.47% of fatal accidents involving bicyclists the other vehicle was going straight.

Table 31: Proposed WATCH-OVER bicyclists-related scenarios

2.3.3. Powered two-wheelers

The highest accident percentage occurs when the other vehicle moves in a straight line or turns left and when the PTW is travelling in straight line or performs a passing manoeuvre on the left. As regards the first impact point, the front part should be considered for the PTW. Cars are the most relevant collision opponents, with lateral side (first option) and frontal side (second one) to be considered as first impact point. Light to heavy trucks have a significant percentage. According to the statistical data and especially to MAIDS results, the vehicle speed mainly considered in WATCH-OVER should be below 50 km/h. Both day and night have to be considered. Dry road covers the largest percentage of accident events. The accident location survey for motorcycles and mopeds shows miscellaneous inputs. A major observation is that there is a higher incidence of fatalities outside the urban areas, and this is reasonable due to higher speeds involved. However the highest percentage of accidents happens in urban environment, which should be the main focus of WATCH-OVER, followed by rural environment as a second option. Within urban areas intersections should be the main focus. All age groups should be considered. Due to the complexity of the scenarios and the different combination of factors in accidents involving PTW, a lot of variables should be considered as a parameter in the WATCH-OVER study, in particular collision opponent and speed, time of day, road conditions, accident location and age group. Major results regarding motorcycles accident analysis are summarised into next table.




34

N. CONSIDERED


1 Accident configuration and first contact point

1. The vehicle moves in a straight line or turns left; PTW is travelling in straight line or performs a passing manoeuvre on the left.

2. PTW into other vehicle impact at intersection. 3. In front of the vehicle or in the left/right side.


Passenger cars (primary option). To be considered as a parameter

3 Collision speed Different options. The vehicle speed mainly considered should be below 50 km/h.

To be considered as a parameter

4 Time of day Day and night. Attention to dusk conditions. To be considered as a parameter

5 Road conditions

Dry road (main option). To be considered as a parameter

6 Accident location

Urban environment (intersections) and rural roads (second option).

To be considered as a parameter


See point 1.

8 Age group of user


Table 32: PTW accident survey outcomes

Therefore the following scenarios have been selected as they are the most common according to previous observations.


REASONING FOR

SELECTING THESE

SCENARIOS

9

PTW impacts from left side into vehicle at intersection, paths perpendicular

10

PTW impacts from right side into vehicle at intersection, paths perpendicular

According to MAIDS 2004, the most frequent accident configuration (9.1%) for accidents involving PTWs was “PTW into OV impact at intersection, paths perpendicular”. Another 6.3% of accidents were “OV into PTW impact at intersection, paths perpendicular”.




35


REASONING FOR

SELECTING THESE

SCENARIOS

11 Vehicle turning left in front of PTW

According to MAIDS 2004, 6.1% of accidents involving PTWs were “PTW overtaking OV while OV turning left”.

12

PTW and vehicle travelling in opposite directions, vehicle turns in front of PTW

According to MAIDS 2004, the second most frequent accident configuration (8.9%) for accidents involving PTWs was “OV turning left in front of PTW, PTW perpendicular to OV path”. Another 8.6% of accidents were “PTW and OV travelling in opposite directions, OV turns in front of PTW, PTW impacting OV”.

Table 33: Proposed WATCH-OVER PTW-related scenarios

3. Selection of Scenarios The definition of scenarios and use cases follows an iterative approach that is conceived to guarantee as much as possible the identification of all relevant scenarios and consequently of all relevant use cases. The starting point is the list of scenarios selected in the accident analysis, that considers all information available from previous studies and from statistical data survey about injuries and fatalities occurred to road users. This method alone would perfectly define all relevant scenarios and use cases if a complete analysis of all the accident cases in the recent years would be available, but due to the limitations in temporal and geographical input availability (minimum 3 year that should cover all European countries) it cannot be considered as a complete and definitive analysis. Moreover accident databases are not complete or even not available with the required level of details, therefore the study can give only an indication of which are the relevant scenarios, but it cannot be exhaustive. The first approach is based on the accident survey and it is represented from an expert brainstorming session that analysed the outcomes of the accident survey and extended the already identified cases completing part of the relevant scenarios by adding relevant and related cases. Again this analysis cannot be considered exhaustive as the experts based the considerations on




36

their experience; this is true even if the team of experts is composed of people that are working in the field of design and development of driving support systems since several years. The second approach is systematic to enable the identification of all possible combinations of relevant scenarios to ensure that the cross section of the two approaches is not missing any of the relevant cases.

3.1. Scenarios from expert brainstorming In the previous paragraph, a review of accident statistical data performed by an examination of latest available information from different databases identified a first set of pre-crash scenarios (accident configurations) most relevant to VRU and the relevant parameters that should be considered by WATCH-OVER. For the aforementioned reasons the accident survey is considered as the starting point of an experts workshop, held in Leonberg, Germany, on the 5th of April 2006, at Robert BOSCH GmbH premises. The participants to the workshop were eleven experts coming from different areas of study and working environments. There were representatives of vehicle manufacturers (cars and motorbikes, 3 in total), OEM (original equipment manufacturers, 2 in total), automotive suppliers (1), research centres (2) and universities (3), coming from several area of interest: software developers, hardware researcher, Human Machine Interface experts, communication specialists, software engineers and experts of software and hardware testing. The focus of the workshop was:

• To discuss about the scenarios reported from accident survey and to identify new scenarios, if necessary.

• To make a first prioritisation of selected scenarios.

• To identify the parameters that will be used in the use cases. In the next sections a description of each item is presented.

3.1.1. Selection of new scenarios

The workshop started from the initial list of scenarios and the preliminary use cases. The list is divided in three parts and it regards the presence of pedestrians, bicyclists and PTW. The accident configurations, collision opponent, collision speed, time of day, weather and road conditions, accident location, first contact point and the age group were reviewed. As a first hint, the participants observed that scenarios involving PTW or bicyclists as a collision opponent to pedestrians were not sufficiently evaluated, because within the available statistical data it was not possible to draw remarks about such scenarios. All experts agreed that the list, even if covering important accident configurations, was missing some important scenarios. The suggestion was to identify new situations related to common or personal experiences in order to include as much accidents configurations as possible. The experts concentrated their attention in scenarios where a car is the collision opponent to a VRU. A first example was the “turning right” situations in the pedestrian-related scenarios and bicycles-related scenarios. The following table describes them.




37

DESCRIPTION SKETCH Vehicle turning right at an intersection, pedestrian crossing the road from the right to the left.

Vehicle on a crossroad turning right, pedal cyclist going straight on bicycle road (parallel with the vehicle).

Table 34: New "turning right" scenarios

Another scenario considered as potentially dangerous is presented in the next table. The bicycle and the vehicle are travelling in opposite directions and the vehicle turns in front of the bicycle.

DESCRIPTION SKETCH Pedal cyclist and vehicle travelling in opposite directions, vehicle turns in front of pedal cyclist.

Table 35: New bicycle scenario

Furthermore, new scenarios were identified where the VRU is hidden from other obstacles. This type of scenarios was considered really important, since the use of the WATCH-OVER system is more essential in such cases. The table below indicates some scenarios proposed during the focus group.




38

DESCRIPTION SKETCH Pedal cyclist occluded from parked cars and vehicle travelling in opposite directions, vehicle turns in front of pedal cyclist.

PTW impacts from left side into vehicle at intersection, paths perpendicular, occluded from parked car.

Table 36: New scenarios with obstacles

The first is similar to the one described in Table 35: here there is the presence of a second car (obstacle) beside the bicycle. As a conclusion of this part of the focus group, a final list of 16 traffic configurations was selected and included in the questionnaire to be submitted to final users. The final list of relevant scenarios is reported here for convenience of the reader.

N. DESCRIPTION SKETCH 1 Pedestrian crossing the road

from the right to the left.

2 Pedestrian crossing the road

from the right to the left occluded from parked cars.

3 Pedestrian crossing the road

from the left to the right occluded from parked cars.




39

N. DESCRIPTION SKETCH 4 Vehicle turning left at an

intersection, pedestrian crossing the road from the right to the left.

5 Vehicle turning left at an

intersection, pedestrian crossing the road from the right to the left occluded.

6 Vehicle turning right at an

intersection, pedestrian crossing the road from the right to the left.

7 Vehicle on a crossroad, pedal

cyclist crossing the road from the right.




40

N. DESCRIPTION SKETCH 8 Vehicle on a crossroad, pedal

cyclist crossing the road from the left.

9 Vehicle on a crossroad turning

right, pedal cyclist moving on bicycle road (parallel with the vehicle) crossing the road from the right.

10 Pedal cyclist occluded from

parked cars and vehicle travelling in opposite directions, vehicle turns in front of pedal cyclist.

11 Pedal cyclist and vehicle

travelling in opposite directions, vehicle turns in front of pedal cyclist.

12 PTW impacts from left side into

vehicle at intersection, paths perpendicular.




41

N. DESCRIPTION SKETCH 13 PTW impacts from left side into

vehicle at intersection, paths perpendicular, occluded from parked car.

14 PTW impacts from right side into

vehicle at intersection, paths perpendicular.

15 Vehicle turning left in front of

PTW.

16 PTW and vehicle travelling in

opposite directions, vehicle turns in front of PTW.

Table 37: Selection of scenarios for the questionnaire submission




42

3.1.2. Prioritisation of scenarios

The second objective of the expert workshop was to priorities the most significant scenarios. This was considered particularly important because it is a first step towards the selection of the most suitable use cases to be studied in the WATCH-OVER framework. The participants expressed their opinion regarding the relevance of the identified scenarios, with a one-by-one selection and investigation of each of them. Every scenario was sketched for all participants at a blackboard and everyone had to answer to two different questions regarding the selected accident situation. Each answer was given independently from other experts and it was filled into a personal chart. First of all the participants were asked to subjectively judge the relevance for road safety of each scenario, by giving a rate from 1 to 7 (1: unimportant - 7: very relevant). Figure 16 presents graphically the mean value obtained from their evaluation. As a second question, it was asked how experts evaluate the adequacy of a cooperative approach to be used for that particular scenario, with the same rate scale (1: unimportant - 7: very relevant). This last aspect was important to understand how much the WATCH-OVER system would be able to improve the efficiency of the VRU recognition and helpful to reduce accidents. Results are presented in Figure 17.

Relevance for road safety of the selected scenario (1: not relevant - 7: very relevant)

5,3

6,1

4,8

3,9

4,6

5

3,73,9

5,8

3,9

5,1

4,7

5,5

4,7

3,7

4,1

0

1

2

3

4

5

6

7

Sc1 Sc2 Sc3 Sc4 Sc5 Sc6 Sc7 Sc8 Sc9 Sc10 Sc11 Sc12 Sc13 Sc14 Sc15 Sc16

mea

n v

alu

e

Figure 16: Workshop prioritisation relevance for road safety

From a first examination of the mean values in the previous figure, the most relevant scenario is the second, i.e. “Pedestrian crossing the road from the right to the left occluded from parked cars” with the rate 6.1. The lowest rate (mean value 3.7) was given to two scenarios, n. 7 and n. 15 (“Vehicle on a crossroad, pedal cyclist crossing the road from the right”, “Vehicle turning left in front of PTW”).




43

Adequacy of the cooperative approach for the selected scenario (1: not relevant - 7: very relevant)

3,9

5,7

5,4

4

4,9

5,3

4,24,1

5,6

3,9

5,4

4,1

5,7

4

3,7 3,7

0

1

2

3

4

5

6

7


mea

n v

alu

e

Figure 17: Workshop prioritisation relevance for the use of a cooperative approach

According again to the mean values, scenario n. 2 (“Pedestrian crossing the road from the right to the left occluded from parked cars”) and scenario n. 13 (“PTW impacts from left side into vehicle at intersection, paths perpendicular, occluded from parked car”) were the most relevant for a cooperative system, with mean value 5.7. The scenarios n. 15 (“Vehicle turning left in front of PTW”) and n. 16 (“PTW and vehicle travelling in opposite directions, vehicle turns in front of PTW”) were judged with the lowest rate (mean value 3.7). With the aim of a more detailed investigation, an inter-agreement index was calculated from participants’ answers elaboration, i.e. the within-group agreement or “r(wg)" index. The r(wg) was assessed using the method proposed by James, Demaree, and Wolf 1984. Essentially, r(wg) is 1 minus the ratio of the observed variance in scores to an expected variance if all responses were random rather than in agreement (i.e., a uniform distribution of responses, equal number of 1s, 2s and 3s from a 3-point response scale). Values nearer to 1.0 reflect agreement, whereas values nearer to zero reflect lack of agreement. With this index it is measured how much the participants who completed the workshop opinion poll agree in their answers to a question or in their opinion. When in the next tables this index is higher than 0.6 then the judgement is highly reliable, if it is higher than 0.7, then the judgement is significant. In other words, the closer this index goes to 1, the most representative the mean value is. If the mean value is high and the r(wg) higher than 0.6, the scenario is considered very important. In the next two figures it is immediately visible the comparison between the mean values calculated from experts answers and the within-group agreement (triangles). The highest the r(wg) index, the most reliable is the mean value.




44

0,50

0,70

0,18

0,64

0,27

0,61 0,61

0,75

0,29

0,530,55 0,54

0,50

0,11

0,53

-0,02

-1

0

1

2

3

4

5

6

7


mea

n v

alu

e

-0,13

0,00

0,13

0,25

0,38

0,50

0,63

0,75

0,88

1,00

r(w

g)

Figure 18: Relevance for road safety, comparison of mean value and r(wg)

In the figure, scenario n. 2 had the highest mean value, 6.1, and its r(wg) index was 0.7, so this judgment was significant. Scenario n. 9 had a mean value of 5.8, but the r(wg) index was below 0.3. Scenario n. 13 had a mean value of 5.5, but in this case the r(wg) index was 0.54. As a consequence situation depicted in scenario n. 13 should be more significant than the one of n. 9. Therefore, the most important scenarios for the road safety aspect were, in order, scenarios n. 1, 2, 6, 12, 13, 14, 16; these scenarios have a mean score greater or equal than 4 and an r(wg) greater or equal than 0.5. Looking at the lowest rates, the r(wg) index for scenario n. 7 was 0.61, and the r(wg) index for scenario n. 15 was 0.11. Therefore, the low grade of the scenario n. 7 should be considered reliable, in contrast with the evaluation of the scenario n. 15, where experts were quite in disagreement.




45

0,09

0,77 0,77

0,61

0,42

0,66

0,62

0,42

0,38

0,25

0,66

0,25

0,72

0,17

-0,11

0,39

-1

0

1

2

3

4

5

6

7


mea

n v

alu

e

-0,13

0,00

0,13

0,25

0,38

0,50

0,63

0,75

0,88

1,00

r(w

g)

Figure 19: Adequacy for cooperative system, comparison of mean value and r(wg)

Observing the previous figure, where both scenarios n. 2 and n. 13 had a mean rate of 5.7, the r(wg) index was higher for the first one (0.77 versus 0.72); therefore, scenario n. 2 should be considered slightly more relevant than scenario n. 13. Scenario n. 9, even if with a significant average value, had a r(wg) index of 0.38, which was quite low; this could be interpreted as this scenario is not important for a certain number of participants. On the other hand both scenarios n. 3 and n. 11 had a mean rate of 5.4; in these scenarios both r(wg) indexes were quite high (0.77 and 0.66), so both of them should be judged as significant. As a conclusion, the most relevant scenarios from the cooperative approach point of view are, in order, scenarios n. 2, 3, 4, 6, 7, 11, 13; these scenarios have been scored with a mean value greater or equal than 4 with a r(wg) greater or equal than 0.5. In the lowest part of the chart, scenarios n. 15 and n. 16, with mean values of 3.7, had the r(wg) indexes respectively of -0.11 and 0.39. The judgements for both scenarios couldn’t be considered as reliable, particularly for the first one. The expert brainstorming continued with the estimation of the technological feasibility of each selected scenario from the point of view of affordability of each scenario with the WATCH-OVER technologies versus the extended cooperative approach. By extended cooperative approach it is meant that the information (detected either by a sensor, or by a communication technology or by both) of the presence of a VRU at risk is propagated to other surrounding vehicles and / or to the infrastructure or to traffic control centres. The extended cooperative approach is out of the scope of WATCH-OVER and the specific application is covered by other EU co-funded projects.




46

SCENARIO

N.

TECHNOLOGICAL

FEASIBILITY WITH

VIDEO SENSOR BASED

DETECTION

TECHNOLOGICAL

FEASIBILITY WITH

COMMUNICATION BASED

DETECTION

OVERALL FEASIBILITY

(FROM A=FEASIBLE TO

D=DIFFICULTLY FEASIBLE)

1 X X A 2 partially X A 3 partially X A

4 X X B 5 partially X C 6 X C 7 partially X B 8 partially X B 9 X C

10 partially X D

11 X X B 12 X C 13 X C 14 X B 15 X D 16 X X B

Table 38: Technical feasibility

For the relevant scenarios identified so far, a table is provided hereafter for convenience of the reader summarising the scenario relevance for road safety, the relevance for the cooperative approach in general and the specific technological feasibility of the application with communication and video technology (not including the propagation of the information to other vehicles or infrastructures). For each scenario a note from the experts is indicated where a specific consideration has been raised.

SCENARIO

N.

RELEVANCE FOR

ROAD SAFETY

RELEVANCE FOR

COOPERATIVE

APPROACH

TECHNOLOGICAL

FEASIBILITY

(A=FEASIBLE,

D=DIFFICULTLY

FEASIBLE)

NOTES (IF ANY)

1 Relevant Not considered as relevant or experts not in agreement

A

2 Relevant Relevant A 3 Not considered as

relevant or experts not in agreement

Relevant A Suggested to be merged into scenario n. 2 as it is mirrored

4 Not considered as relevant or experts not in agreement

Relevant B


Not considered as relevant or experts not in agreement

C

6 Relevant Relevant C 7 Not considered as


Relevant B

8 Not considered as relevant or experts

Not considered as relevant or experts

B




47

SCENARIO

N.

RELEVANCE FOR

ROAD SAFETY

RELEVANCE FOR

COOPERATIVE

APPROACH

TECHNOLOGICAL

FEASIBILITY

(A=FEASIBLE,

D=DIFFICULTLY

FEASIBLE)

NOTES (IF ANY)

not in agreement not in agreement



C



D Suggestion to be removed as very rare to occur


Relevant B


C

13 Relevant Relevant C 14 Relevant Not considered as


B



D Suggestion to be removed as it has to be addressed by lateral assistance cooperative and stand alone applications


B

Table 39: Overview of the scenario relevance for different aspects

3.1.3. Identification of parameters

In the last part of the workshop experts selected the most relevant parameters to be used for the estimation of the project use cases. The accident survey recognised different sets of parameters as the most important variables to be taken into account per each group of the three different VRU-related scenarios (pedestrian, pedal cyclists and powered two-wheelers), as indicated in the following list. Pedestrian-related incidents:

• Collision speed

• Time of day

• Accident location

• Pedestrian age group Cyclist-related incidents:

• Collision speed


• Cyclist age group PTW-related incidents:

• Collision opponent

• Collision speed




48

• Time of day

• Road conditions


• Two-wheelers drivers’ age group The aim of this part of the work was to introduce a methodology that shall simplify the study of the use cases. It was proposed to reconsider or redefine some of the previous variables (and their characterisation), in order to make possible a clear parameterisation of the uses cases with mean of a risk level, calculated by giving different weight to the use cases parameters. The use cases parameters should be considered as level of risk which is unique per each use case, based on different weights that are given to the parameters. According to the workshop discussion and for an easier use case evaluation, all parameters shall be the same for all categories (Pedestrian, bicyclists, PTW). Seven possible parameters were identified to be appropriate for the WATCH-OVER framework:

1. Vehicle speed 2. Velocity of VRU 3. Time to collision 4. Time of day 5. Weather conditions 6. Traffic environment and density 7. Visibility of VRU

During the debate it emerged that also the direction that the VRU has towards the colliding area should be known if possible (relative trajectories), in order to include more detailed cases. With mean of the time to collision, the distance between the two opponents can be calculated. The fourth variable, time of day, shall be divided into the four key options dawn, day, dusk and night. Furthermore, two of the parameters presented were discussed during the workshop, but it was proposed not to include them in the use cases analysis, as explained below. Visibility of the VRU This parameter is difficult to evaluate, since it is based on a personal judgment and also the level of visibility could change very quickly. In SAVE-U project, the approach followed was to divide in three cases, according to the level of occlusion of the VRU, i.e.:

• None occluded (maximum 10% of occlusion);

• Partly occluded (maximum 50% of occlusion);

• Occluded (more than 50% of occlusion). In some of the already selected scenarios there is the presence of an obstacle, therefore the occlusion parameter has already been taken into account. Traffic environment and density All the scenarios described in the previous section could be applied in urban and extra-urban (or rural) traffic environment. Therefore, this parameter should not be considered for a prioritisation analysis. In addition, this parameter is partly covered by the “vehicle speed” parameter, since, if the vehicle speed is less or equal to 50 km/h, it could be considered that the car is moving in an urban road, and if the vehicle speed is more than 50 km/h the vehicle should be moving in a rural road. As what is relevant is the relative speed and trajectories of the opponents, this parameter is considered as not to be included into the use cases. Additionally the experts stated that for all selected scenarios the fact that only one VRU is foreseen in the sketch does also include all cases in which there is a group of VRU, for example one pedestrian crossing the road is as dangerous as a number of pedestrians crossing the road at the same time and in this case only one warning has to be provided to the driver.




49

3.2. Scenarios from methodical analysis An additional approach to evaluate and select the scenarios is a systematic analysis of all possible actors, relative dynamics or interactions and parameters that should be considered for the project application. A first set of assumptions are done by the team of experts on the basis of general observations that are to be considered as pre-requisites for all scenarios and use cases. Assumptions are needed to limit the number of possible combinations to a significant but complete set of scenarios, otherwise obviously the number of combinations is infinite, therefore these assumptions should be treated as one way and not the unique way to treat the needed simplifications.

First assumption:

• the VEHICLE category includes trucks, cars, motorbikes (motorbikes are inserted in this class even if they are vulnerable users for their comparable speeds to cars and trucks);

• the Vulnerable User category includes bicycles and pedestrians (for their comparable speeds which is typically much slower than the speeds of the vehicle category).

Second assumption:

• Cars and trucks are treated in the same way in this definition of scenarios and use cases as in respect to this application they have comparable speeds and comparable blind spots

Third assumption:

• Parameterisation is given on the assumption of: 1 = low dangerousness 2 = medium dangerousness 3 = high dangerousness.

Among different scenario variables, there are entities that are parameterised or not. The subdivision is done as follows. Not parameterised variables TYPE OF VEHICLES and of VULNERABLE ROAD USERS CAT = Cars and trucks PTW = Motorbikes and moped BIC = Bicycles PED = Pedestrians TYPE OF ROAD STR = Straight road CUR = Curve (with partial occlusion of the vehicle in respect to the VRU and vice versa) CRO = Crossing ROU = Roundabout RELATIVE TRAJECTORIES PCT = Perpendicular crossing trajectories POT = Parallel overtaking trajectories RTT = Respective turning trajectories Parameterised variables A. Vehicle speed (cars, trucks, motorbikes) A.1 Less then vehicle speed limit A.2 10% more then vehicle speed limit A.3 50% more then vehicle speed limit B. Vulnerable Road User speed (pedestrian, bicycle) B.1 Slow (walking pedestrian, bicycle’s speed less then 25 km/h)




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B.2 Fast (running pedestrian, bicycle’s speed more then 25 km/h) C. Time to Collision C.1 Detection time > time to collision (avoidable accident) C.2 Detection time < time to collision (unavoidable accident; severity can be reduced) D. Time of day D.1 Day D.2 Dusk / Dawn D.3 Night E. Weather conditions affecting road conditions and/or visibility E.1 Good E.2 Road slipperiness increased and / or visibility reduced but it’s still possible for the vehicle to stop before the accident with the VRU E.3 Road slipperiness increased and / or visibility reduced and it is only possible to reduce accident severity F. Traffic density F.1 Rare traffic = sufficient space for collision avoidance / mitigation manoeuvres F.2 Dense traffic = limited space for collision avoidance / mitigation manoeuvres G. Visibility of the VRU G.1 VISIBLE (maximum 10% of occlusion) G.2 PARTLY OCCLUDED (maximum 50% of occlusion) G.3 OCCLUDED (more than 50% of occlusion) Type of accidents by vehicles and vulnerable users involved addressed by WATCH-OVER In the following table a further simplification is introduced by considering the different opponents to be one or more involved per each category (for instance: an accident involving two pedestrians is treated in the same way as accidents that involve one pedestrian).

CAT PTW BIC PED CAT Not addressed CAT-PTW CAT-BIC CAT-PED

PTW PTW-CAT PTW-PTW PTW-BIC PTW-PED

BIC BIC-CAT BIC-PTW Not addressed Not addressed

PED PED-CAT PED-PTW Not addressed Not addressed

Table 40: Accident opponents combinations

Table 40 leads to a total number of combinations of opponents in an accident listed hereafter:

1. CAT-PTW 2. CAT-BIC 3. CAT-PED 4. PTW-PTW 5. PTW-BIC 6. PTW-PED

Other combinations are symmetrical with respect to these in the list. Type of accidents by vehicles and vulnerable users involved and by type of road addressed by WATCH-OVER As four different type of road were selected (STR, CUR, CRO and ROU), the combination with the previous items is 6 * 3 = 24 different scenarios. The scenarios are listed in Table 41.




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STR CUR CRO ROU

CAT-PTW CAT-PTW-STR CAT-PTW-CUR CAT-PTW-CRO CAT-PTW-ROU

CAT-BIC CAT-BIC-STR CAT-BIC-CUR CAT-BIC-CRO CAT-BIC-ROU

CAT-PED CAT-PED-STR CAT-PED-CUR CAT-PED-CRO CAT-PED-ROU

PTW-PTW PTW-PTW-STR PTW-PTW-CUR PTW-PTW-CRO PTW-PTW-ROU

PTW-BIC PTW-BIC-STR PTW-BIC-CUR PTW-BIC-CRO PTW-BIC-ROU

PTW-PED PTW-PED-STR PTW-PED-CUR PTW-PED-CRO PTW-PED-ROU

Table 41: Accident opponents and type of road

In summary 24 different types of accidents are identified. Type of accidents by vehicles and vulnerable users involved, by type of road and by relative trajectories, addressed by WATCH-OVER. As three different categories of relevant trajectories have been identified to be relevant (PCT, POT, RTT), the combination with the already identified scenarios is 24 * 3 = 72 different scenarios. They are listed in Table 42.

PCT POT RTT

CAT-PTW-STR PCT1 - CAT-PTW-STR POT1 - CAT-PTW-STR RTT1 - CAT-PTW-STR

CAT-BIC-STR PCT2 - CAT-BIC-STR POT2 - CAT-BIC-STR RTT2 - CAT-BIC-STR

CAT-PED-STR PCT3 - CAT-PED-STR POT3 - CAT-PED-STR RTT3 - CAT-PED-STR

PTW-PTW-STR PCT4 - PTW-PTW-STR POT4 - PTW-PTW-STR RTT4 - PTW-PTW-STR

PTW-BIC-STR PCT5 - PTW-BIC-STR POT5 - PTW-BIC-STR RTT5 - PTW-BIC-STR

PTW-PED-STR PCT6 - PTW-PED-STR POT6 - PTW-PED-STR RTT6 - PTW-PED-STR

CAT-PTW-CUR PCT7 - CAT-PTW-CUR POT7 - CAT-PTW-CUR RTT7 - CAT-PTW-CUR

CAT-BIC-CUR PCT8 - CAT-BIC-CUR POT8 - CAT-BIC-CUR RTT8 - CAT-BIC-CUR

CAT-PED-CUR PCT9 - CAT-PED-CUR POT9 - CAT-PED-CUR RTT9 - CAT-PED-CUR

PTW-PTW-CUR PCT10 - PTW-PTW-CUR POT10 - PTW-PTW-CUR RTT10 - PTW-PTW-CUR

PTW-BIC-CUR PCT11 - PTW-BIC-CUR POT11 - PTW-BIC-CUR RTT11 - PTW-BIC-CUR

PTW-PED-CUR PCT12 - PTW-PED-CUR POT12 - PTW-PED-CUR RTT12 - PTW-PED-CUR

CAT-PTW-CRO PCT13 - CAT-PTW-CRO POT13 - CAT-PTW-CRO RTT13 - CAT-PTW-CRO

CAT-BIC-CRO PCT14 - CAT-BIC-CRO POT14 - CAT-BIC-CRO RTT14 - CAT-BIC-CRO

CAT-PED-CRO PCT15 - CAT-PED-CRO POT15 - CAT-PED-CRO RTT15 - CAT-PED-CRO

PTW-PTW-CRO PCT16 - PTW-PTW-CRO POT16 - PTW-PTW-CRO RTT16 - PTW-PTW-CRO

PTW-BIC-CRO PCT17 - PTW-BIC-CRO POT17 - PTW-BIC-CRO RTT17 - PTW-BIC-CRO

PTW-PED-CRO PCT18 - PTW-PED-CRO POT18 - PTW-PED-CRO RTT18 - PTW-PED-CRO

CAT-PTW-ROU PCT19 - CAT-PTW-ROU POT19 - CAT-PTW-ROU RTT19 - CAT-PTW-ROU

CAT-BIC-ROU PCT20 - CAT-BIC-ROU POT20 - CAT-BIC-ROU RTT20 - CAT-BIC-ROU

CAT-PED-ROU PCT21 - CAT-PED-ROU POT21 - CAT-PED-ROU RTT21 - CAT-PED-ROU

PTW-PTW-ROU PCT22 - PTW-PTW-ROU POT22 - PTW-PTW-ROU RTT22 - PTW-PTW-ROU

PTW-BIC-ROU PCT23 - PTW-BIC-ROU POT23 - PTW-BIC-ROU RTT23 - PTW-BIC-ROU

PTW-PED-ROU PCT24 - PTW-PED-ROU POT24 - PTW-PED-ROU RTT24 - PTW-PED-ROU

Table 42: Type of accidents considering category, type of road and relative trajectories

Type of accidents by vehicles and vulnerable users involved, by type of road, by relative trajectories and by parameter characterisation addressed by WATCH-OVER. The identified scenarios have to be compared (in terms of relevance) with 7 parameters (from A to G type of parameters); each parameters can be in 2 (B, C and F) or in 3 (A, D, E and G) states. All possible combinations are not singularly considered, as their number is vast, but they are listed grouped by possible categories into the next table.




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Code by type of trajectory

Type of accident A. Vehicle

speed

B. Vulnerable Road User

speed

C. Time to Collision

D. Time of day

E. Weather conditions

F. Traffic density

G. Visibility of the VRU

PCT 1 CAT-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 2 CAT-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 3 CAT-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 4 PTW-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 5 PTW-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 6 PTW-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 7 CAT-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 8 CAT-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 9 CAT-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 10 PTW-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 11 PTW-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 12 PTW-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 13 CAT-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 14 CAT-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 15 CAT-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 16 PTW-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 17 PTW-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 18 PTW-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 19 CAT-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 20 CAT-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 21 CAT-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 22 PTW-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 23 PTW-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

PCT 24 PTW-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 1 CAT-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 2 CAT-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 3 CAT-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 4 PTW-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 5 PTW-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 6 PTW-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 7 CAT-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 8 CAT-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 9 CAT-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 10 PTW-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 11 PTW-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 12 PTW-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 13 CAT-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 14 CAT-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 15 CAT-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 16 PTW-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 17 PTW-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 18 PTW-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 19 CAT-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 20 CAT-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 21 CAT-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 22 PTW-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 23 PTW-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

POT 24 PTW-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 1 CAT-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 2 CAT-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 3 CAT-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3




53



speed


speed


D. Time of day


F. Traffic density

G. Visibility of the VRU

RTT 4 PTW-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 5 PTW-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 6 PTW-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 7 CAT-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 8 CAT-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 9 CAT-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 10 PTW-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 11 PTW-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 12 PTW-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 13 CAT-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 14 CAT-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 15 CAT-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 16 PTW-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 17 PTW-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 18 PTW-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 19 CAT-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 20 CAT-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 21 CAT-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 22 PTW-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 23 PTW-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

RTT 24 PTW-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3 1, 2 1, 2, 3

Table 43: Parameters combination for type of accident

These scenarios are not prioritised. They are made available to the experts for a final evaluation of the completeness of the selected scenarios. These considerations will be done in paragraph 5.1 where the final conclusions about scenarios selections will be drawn.

4. User requirements The user requirements represent how an end user would like to interact with the WATCH-OVER system and which main features should be present. This aspect is really important for a correct design and implementation of the system hardware and software architecture and it has to be considered since the beginning of the project. The methodology that has been chosen to understand users’ preferences is to administer questionnaires to “final non technical expert users”. The involved users are drivers who regularly move with a car, users of motorbikes and bicyclists. The process followed is divided in three parts. The first includes a set of questions to be inserted in an ad-hoc questionnaire, and this has been done during a dedicated expert workshop. In the second part the questionnaire is administered to a large number of users who completed the questionnaire on-line (via the WATCH-OVER web pages). In the third part the answers inserted in a database are studied and evaluated with mean of statistical analysis. In the next paragraphs the first and the third part previously listed are presented.




54

4.1. Questionnaire preparation The state of the art study highlighted that only very few inputs can be considered for the WATCH-OVER user needs analysis. For this reason the decision was to estimate potential users’ desiderata with a detailed investigation tasks. During an experts workshop organised in Leonberg, Germany, a focus group discussed on user needs and on how to determine them. The best solution was found in the proposal of a specific questionnaire where the questions should focus on practical issues, such as if the user would like to receive information about the presence of vulnerable road users or warnings about potential accidents, in which way he/she would like to receive the information. According to the results of the focus group, one part of the questionnaire was focussed on the examination of special situations or accident configurations, in order to recognise how dangerous some particular scenarios were considered from the users. The identified scenarios were first identified in the accident survey and then better specified during the workshop. This part was important to understand how much support is needed depending on the external situation (and situation awareness) and also which are the most relevant use cases to be considered in the WATCH-OVER framework. The final page of the questionnaire was open to let the person suggest new scenarios or situations that didn’t emerge in previous listed scenarios. The draft version of the questionnaire was defined and shared among experts during the workshop, while the final version was implemented later on for being accessible from WATCH-OVER web pages. A significant input coming from the focus group was how to implement the HMI in order to limit the number of false alarms or to completely avoid them. This aspect is really relevant because it could undermine the overall project outcome. The objective of the discussion was to limit the drawbacks or inadequacies that could emerge during the implementation or the use of the WATCH-OVER system. The level of drivers’ situation awareness (SA) was divided in two categories:

• non occluded (completely aware and not distracted)

• occluded (not aware by occlusion or distraction) It was considered very important to follow coherence among SA and warnings and to avoid redundancy. The system should “evaluate” the risk level continuously. When the risk level is approaching a specified threshold, the system should warn the driver or eventually the VRU. These thresholds should be identified according to the risk levels. It is necessary to avoid the false alarms in all cases, if possible. The following representation illustrates the approach that should be followed.

HMI reference stack Warning (alarm) _____________ Potential alarm _____________ NO alarm

This foreseen approach is introduced in order to highlight the relevant risk of developing a system that potentially could disturb the driver / VRU instead of being able to help him or her. If the HMI interface is too pervasive, with intensive output presented to the user, especially audio or visual with capturing feature, it may lead to the switching off of the power supply. The final version of the questionnaire is developed and implemented as an on-line application with animations of the scenarios. It is divided into four parts:

Application implementation should use a bottom-up approach: the risk level is continuously monitored, and after a

certain number of alarm “steps” exceeds a threshold (or different thresholds) an input or a warning or an alarm should

be given to the driver / VRU.




55

• PART A consists of questions related to personal issues for the respondents’ current driving status.

• PART B includes questions regarding user’s preferences for HMI modalities.

• PART C introduces 16 road scenarios, regarding accidents that could involve pedestrians, bicyclists and powered two-wheelers. The evaluation of each scenario is performed by answering specific questions, such as the level of support per scenario, the type of support preferred.

• In PART D, the respondents were asked to add descriptions of other important scenarios not mentioned in PART C.

4.2. Questionnaire results The user survey was done with the aim to capture the users’ requirements and their evaluation of the proposed scenarios. The questionnaire was accessible through the WATCH-OVER web site and answers were stored in a MySQL database. Each partner invited a certain number of users, mostly active drivers or experts in order to complete the questionnaire. In total 154 people from 10 different countries (Italy, Germany, Greece, Austria, the Netherlands, France, Poland, Switzerland, Czech Republic and India) completed the questionnaire.

4.2.1. Respondents sample

In total 121 males and 33 females answered the questionnaire, as shown below.

Respondents' gender distribution

79%

21%

Male

Female

Figure 20: Respondents’ gender distribution.

The respondents’ age distribution is given below:

• The majority of the respondents, 108 out of 154, belong in the age group of 25-39 years old.

• 30 out of 154 of the respondents belong in the age group 40-45 years old.

• 10 out of 154 are below 25 years old.

• 5 out of 154 are 55=65 years old.

• 1 of 154 is > 66 years old. It is important that all these age categories are represented, besides the elderly and the very young drivers, in the sample, since they have different driving characteristics and behaviours.




56

Respondents' age distribution

71%

3% 6%

1%

19% < 25

25-39

40-54

55-65

>66

Figure 21: Respondents’ age distribution.

The highest percentage of the respondents, 60 out of 154, is driving since more than 16 years, and only 10 out of 154 are drivers since less than 5 years. This observation leads to the conclusion that the respondents of the WATCH-OVER questionnaire are experienced drivers.

Years of driving

6%

25%

29%

40% 0-5 years

6-10 years

11-15 years

> 16 years

Figure 22: Respondents’ years of driving.

In order to have a more detailed view about the driving experience of the respondents, the questionnaire included questions regarding the kilometres driven in the last year and an estimation of the percentage of the kilometres driven on different road types (i.e. motorways, rural roads, urban roads). 153 persons answered the question about last year mileage. 49 out of 153 of the respondents had driven 15.000 to 25.000 km last year and only 19 out of 153 had driven less than 5.000 km last year.




57

Last year driven kilometers

12%

16%

21%33%

18%< 5000 kms

5000-10000 kms

10000-15000 kms

15000-25000 kms

>25000 kms

Figure 23: Last year driven kilometres.

According to the answers of the respondents, as a mean value 39% of their driven kilometres are on motorways, 33% are on rural roads and 28% are on urban roads. These percentages are not much different, leading to the conclusions that all road types are used equally by the respondents.

Percentage of kilometers driven on different road types

28%

33% 39%Motorways (%)

Rural roads (%)

Urban roads (%)

Figure 24: Percentages of the kilometres driven on different road types.

An interesting result is that only 49 from 154 respondents (32%) answered whether they had any accident or near-accident involving a VRU in the past. 39 out of 49 answered that they were not involved in such an accident / near-accident, and 10 out of 49 replied that they were involved in such an accident or near-accident. The majority of the respondents, 67.3%, specified that their cars are equipped with anti lock braking system / traction control, 13.1% of the respondents indicated that their car is equipped with navigation system and 10.1% of the respondents’ car is equipped with speed adapter.




58

4.2.2. Requirements regarding system output

Within this section of the questionnaire, the respondents were asked to indicate their preferences regarding the WATCH-OVER system output, namely when to give information / warning and how to give it. In case of no accident risk First of all the respondents answered to the question whether they would like to be informed by the system about the presence of a vulnerable road user, even if there is no accident risk. The majority of them (89 out of 150) would not like to be informed in that case, and 61 out of 150 would like to be informed in that case.

Would you like to be informed about the presence of VRUs

(location, distance), if there is no accident risk?

41%

59%

Yes

No

Figure 25: Users’ preferences for information, if there is no accident risk.

The respondents that stated that they would like to be informed in such a case further specified the type of information that they would like to receive about the vulnerable road user. Among them 51% would prefer to receive information regarding the distance of the vulnerable road user and 38% indicate that they would also like to receive information regarding the heading of the user. 11% of the respondents suggested other type of information that they would like to receive, such as:

• Relative position.

• Weather.

• Height of the pedestrian.

• Momentum.

• Location and position of the vulnerable road user.




59

Type of information about the vulnerable road user

4937

11

11,34%

38,14%

50,52%

0

10

20

30

40

50

60

Distance Heading other

Nu

mb

er

of

an

sw

ers

Figure 26: Users’ preferences for type of information, if there is no accident risk.

Furthermore, the respondents were asked to specify how they would prefer to receive this information. 86 answers were received for this question. The majority of respondents (47) prefers to be informed by an icon on display, 22 by a tone or beep, 15 by a spoken message and 10 by LED (Light Emitting Diode). In addition, other suggestions were proposed from 6 respondents, such as the use of a map.

Ways of providing information, in case of no accident risk

2215

10

47

6

6,98%

54,65%

11,63%17,44%

25,58%

0

10

20

30

40

50

Tone/Beep Spoken message LED Icon on display Other

Nu

mb

er

of

an

sw

ers

Figure 27: Users’ preferences for information means, if there is no accident risk.

112 respondents answered the question about the location in the car where the received visual information should appear. The majority of them, 70, prefers the head up display, 38 of the respondents indicate the instrument cluster and 31 the central console. Another 6 of the respondents indicate other locations for the appearance of the visual information, such as a bitmap display, the windscreen.




60

Location of visual information

38 31

70

64,14%

48,28%

21,38%26,21%

0

20

40

60

80

Instrument

cluster

Central console Head up display Else

Figure 28: Users’ preferences for location of visual information, if there is no accident risk.

In case of accident risk Another important issue surveyed through the questionnaire was the induction of the warnings by the system, about possible accidents due to the presence of the vulnerable road user. The great majority of respondents, 135 out of 149, would like to receive warnings in case of accident risk. Only 14 out of 149 would not like this functionality.

Would you like to receive warnings by the system about possible

accidents due to the presence of vulnerable road users?

91%

9%

Yes

No

Figure 29: Users’ preferences for warning, if there is accident risk.

Furthermore, the respondents were asked to specify how these warnings should be provided by the system. 137 respondents answered this question. The majority of them, 84, suggests that this warning should be a tone or a beep, 72 suggest an icon on the display, 35 indicate a spoken message and 22 a LED. 12 respondents make other suggestions, such as vibration on the driver seat or seat-belt, the use of a map.




61

Ways of providing warning in case of accident risk

84

3522

72

12

5,33%

32,00%

9,78%

15,56%

37,33%

0

10

20

30

40

50

60

70

80

90

Tone/beep Spoken

message

LED Icon on display Other

Figure 30: Users’ preferences for means of warning, if there is accident risk.

Willingness to have Finally, the respondents were asked whether they are interested to have such a system in their car. The majority of respondents, 139 out of 149, answered that they would like to have such a system, and only 11 out of 149 would not be interested in such a system.

Would you like to have such a system in your car?

93%

7%

Yes

No

Figure 31: Users’ willingness to have such a system.

4.2.3. Evaluation of scenarios

Within this section of the questionnaire, each one of the 16 selected scenarios was presented to the user in terms of a graphical animation. Then, the user was asked to evaluate each specific scenario by answering different questions, regarding the estimated frequency of this scenario, the level of support and intervention needed per scenario, and the circumstances under which support would be preferred (i.e. vehicle speed, time of the day, weather conditions). Regarding the estimated frequency of each scenario, users were asked if they think that this scenario can often occur. They were asked to give an answer in a 5 scale from “Very rarely” (-2) to “Very often” (+2), with 0 meaning “Neither rarely nor often”. The results are given below, where the mean values of the ratings for each scenario are provided together with their standard deviation. The standard deviation is a measure of how spread out is the considered data. If the standard deviation covers a small range around the mean value of the evaluation ratings for a specific




62

scenario, then these ratings are not much different from each other, i.e. the respondents have the same opinion for the evaluation of this scenario.

Evaluation of the frequency occurrence of each scenario in real road

situations

0,536

0,534

0,056

0,338

-0,013

-0,001

0,220

0,116

0,017

-0,325

0,026

-0,024

-0,034

0,034

0,081

0,001

-0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8

Sc1

Sc2

Sc3

Sc4

Sc5

Sc6

Sc7

Sc8

Sc9

Sc10

Sc11

Sc12

Sc13

Sc14

Sc15

Sc16

Frequency (-2: Very Rarely, +2 Very Often)

PE

DE

ST

RIA

NS

BIC

YC

LIS

TS

PT

W

Figure 32: Frequency occurrence of each scenario in real traffic situations.

Users rated scenario n. 1 as more frequent than the others (mean rating 0.536), followed by scenario n. 2 (0.534), 4 (0.338), 7 (0.22) and 8 (0.116). On the contrary, scenario n. 10 is rated as rather rare (mean rating -0.325). Considering the reported figures, the following scenarios are the most frequently appearing in real traffic situations per each related VRU category, as estimated from respondents:

• In scenarios related to pedestrians, the most frequent are scenarios n. 1 and 2.

• In scenarios related to bicyclists, the most frequent is scenario n. 7.

• In scenarios related to PTW, the most frequent are scenarios n. 15 and 14. An important detail, derived from the evaluation of the scenarios, is that the respondents believe that the scenarios related with pedestrians appeared more often in real traffic situations than the ones with bicyclists and powered two-wheelers.




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Evaluation of the frequency occurrence of scenarios per

VRU related category

0,241

0,011 0,012

0

0,05

0,1

0,15

0,2

0,25

0,3

Scenarios with

pedestr.

Scenarios with bicycl. Scenarios with PTW

Figure 33: Frequency occurrence of scenarios per VRU related category.

In order to compare the means of the ratings of each scenario, the t-test was performed. This t-test assesses whether the means of two groups are statistically different from each other (William M. Trochim, Cornell University). The t-test is often the most appropriate statistical test to use in order to compare a continuous outcome variable in two independent groups. The ratings of all scenarios have been compared with each other by using this test. The values indicated if the ratings of the two scenarios were scientifically different. The results confirm that there are significant differences among the ratings of the scenarios. For example, the ratings of scenario n. 2 are significantly different to the ratings of all other scenarios, except scenarios n. 1, 4, 7. Level of support needed per scenario Users were then asked how much support they would need for each scenario. The answers were given in a scale from -2 (very little) to +2 (very big), where 0 means neither little nor big. The results are given below, where the mean values of the ratings for each scenario are provided together with their standard deviation.




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Evaluation of support needed for each scenario

-0,0001

0,5676

0,3357

-0,1319

-0,0100

0,0001

0,0933

0,0966

0,1004

0,2500

0,0789

0,0142

0,2466

0,0345

0,2847

0,0201

-0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8

Sc1

Sc2

Sc3

Sc4

Sc5

Sc6

Sc7

Sc8

Sc9

Sc10

Sc11

Sc12

Sc13

Sc14

Sc15

Sc16

Support needed (-2: Very Little, +2 Very big)

PE

DE

ST

RIA

NS

BIC

YC

LIS

TS

PT

W

Figure 34: Evaluation of support needed in each scenario.

Users responses indicated that more support is needed in the case of scenario n. 2 (mean rating 0.57), followed by scenario n. 3 (0.34), 15 (0.28), 10 (0.25) and 13 (0.246). On the contrary, the respondents need rather little support of the system in scenario n. 4 (mean rating -0.13) and scenario n. 5 (mean rating -0.01). Considering the Figure 34, the following scenarios are indicated as important ones per each related VRU category, since more support is needed for them than the others:

• In scenarios related to pedestrians, more support is needed by the system in scenario n. 2.

• In scenarios related to bicyclists, more support is needed by the system in scenario n. 10.

• In scenarios related to PTW, more support is needed by the system in scenarios n. 15 and 13.

An important detail, derived from the evaluation of the scenarios, is that the respondents believe that more support is needed of the system in case where pedestrians are involved, less when there are bicyclists and even less when there are powered two-wheelers involved.




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Evaluation of support needed in scenarios per VRU related

category

0,1269

0,1238

0,1200

0,116

0,118

0,12

0,122

0,124

0,126

0,128

Scenarios with

pedestr.

Scenarios with

bicycl.

Scenarios with

PTW

Figure 35: Evaluation of support needed in scenarios per VRU related category.

Again t-tests have been performed on the ratings of each scenario. The results confirm that there are significant differences among the ratings of the scenarios. For example, the ratings of scenario n. 2 are significantly different to the ratings of all other scenarios, except scenarios n. 3, 10, 13, 15. Type of support needed per scenario The next question refers to the type of support needed per scenario, whether the respondents would like to receive a warning only in case of accident risk, information even in case of no accident risk, both or no intervention at all. The results are given below. The majority of the respondents indicated that they want to be warned only in case of accident risk for all scenarios. Furthermore, according to the answers of the respondents, a very small percentage of them would not like any intervention by the system at all.

Level of system intervention required per scenario

0

10

20

30

40

50

60

70

80

Sc1 Sc2 Sc3 Sc4 Sc5 Sc6 Sc7 Sc8 Sc9 Sc10 Sc11 Sc12 Sc13 Sc14 Sc15 Sc16Nu

mb

er

of

an

sw

ers

/ N

um

ber

of

resp

on

den

ts

(%)

Warning only in case

of accident risk

Information about

vulnerable road

users, even if no

accident risk existsBoth warning and

information in all

cases

No intervention

Figure 36: Level of system intervention required, per scenario.

When concurrently considering the answers which correspond to “Information about vulnerable road users, even if no accident risk exists” and “Both warning and information in all cases”, the following figure comes out. From this, one can conclude that in most scenarios users would also like to receive information, even if no accident risk exists.




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Level of system intervention required per scenario

0

10

20

30

40

50

60

70

80


Nu

mb

er

of

an

sw

ers

/ N

um

ber

of

resp

on

den

ts (

%)

Warning only in case

of accident risk

Information about

vulnerable road

users, even if no

accident risk exists

AND Both warning

and information in all

cases

Figure 37: Warning vs informing; respondents’ attitudes.

Circumstances under which support is needed per scenario The respondents were asked to specify in which car speed per scenario they need support from the system. Almost for all scenarios, most answers fall in the 30-50 km/h range. However, for scenario n. 1 and for scenario n. 15, most answers fall in the range of 50-70 km/h, according to the respondents’ opinion. Especially for scenario n. 15, a lot of answers also fall in the range > 70 km/h. In fact this scenario has been evaluated by experts to be out of scope in respect to the WATCH-OVER aim as it is addressed by both stand alone and cooperative lateral assistance systems.

Car speed where support is needed

0

10

20

30

40

50

60

70

80

90

100


Scenarios

Nu

mb

er

of

an

sw

ers

/ N

um

ber

of

resp

on

den

ts (

%)

<30km/h

30-50km/h

50-70km/h

>70km/h

Figure 38: Car speed in which support is required, per scenario.

Users were also asked about the time of day at which they would need more support by the system per scenario. According to their answers, night gets more answers in all scenarios, followed by dusk. Anyway, the differences are not significant, since more than 50% of respondents




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select all other options, a percentage which can not be ignored. Thus, one can conclude that all day times are important and the system should be developed and designed for all day times.

Time of day where support is needed

0

20

40

60

80

100

120


Scenarios

Nu

mb

er

of

an

sw

ers

/ N

um

ber

of

resp

on

den

ts (

%)

Dawn

Day

Dusk

Night

Figure 39: Time of the day in which support is needed, per scenario.

Finally, the respondents specified the weather conditions where they would need support by the system. Rain and fog receive equally high answers, and therefore these weather conditions should be considered as the most important ones for all scenarios. However, as in the case of day time, fine weather should not be neglected since in almost all cases more than 50% of respondents select this option too.

Weather conditions where support is needed

0.00

20.00

40.00

60.00

80.00

100.00

120.00


Scenarios

Nu

mb

er

of

an

sw

ers

/ N

um

ber

of

resp

on

den

ts (

%

Fine weather

Rain

Fog

Figure 40: Weather conditions in which support is needed, per scenario.

By considering the analysis above, the car speed, the day time and the weather conditions are really important parameters for all respondents and therefore should be thoroughly considered in all scenarios and use cases.




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4.2.4. Suggestions from the respondents

Within the final section of the questionnaire, the respondents were asked to suggest other important scenarios not included in the previous section, regarding accidents that could involve vulnerable road users. 75% of the respondents (115 out of 154) agreed that the scenarios previously mentioned are the most important ones, whereas 35% of the respondents (39 out of 154) proposed other important scenarios as well. Their most important (corresponding to multiple user hints) suggestions are listed in the following table.

N. DESCRIPTION 1 Reversing in rural areas (from parking places, etc.). 2 All possible accidents when car is going back (< 30 km/h): a child on the rear, very close to the

car, not visible because of his/her height or someone that crosses the street close to the rear of the car.

3 To get out from a roundabout: car turns right while a pedestrian or a bicycle is crossing the road the car is turning in.

4 Pedestrians crossing a road while a motorbike is approaching. 5 When the PTW runs parallel with car direction and it is going to overtake the car from the right

side. 6 Person driving a bicycle on the car lane on a rural road. 7 Vulnerable road user present alongside a street at night. Not necessarily any special action

performed by vulnerable road user. In this case: warning only. 8 Bicyclist is overtaking vehicle from the left side, especially in one-way streets. Bicyclist can be

overlooked by vehicle driver, e.g. if he/she turns left or is looking for a parking space on the left side.

9 A truck that braches off to the right with a bicycle on the right side. 10 Entering the street from a parking slot or from a private ground. 11 Bus still stopped at the bus stop and the passengers, got off from it, crossing the road in front of

the bus.

Table 44: Scenario suggested from questionnaire respondents

Some of the indicated scenarios are already included in the scenarios administered in the questionnaire (they are simply an extension) while all additional scenarios will not be included in the use case description as no ranking can be drawn from data available; these scenarios will be taken into consideration during the testing phase. Other suggestions follow below:

• A car user, after the parking, opens the car door in front of a biker that is running near the parked cars.

• A motorcycle, hidden by a truck/car, is suddenly changing lanes in front of a car.

• Cyclist that overtakes cars, when they are stopping due to traffic light.

• A bicycle lane parallel to the road. At a crossing a bicycle and a vehicle are turning right, but the driver has overseen the cyclist and is cutting the corner.

• Rear-end type of collisions (overlooking) frontal collisions while overtaking (overlooking)

• Warning for presence of animals on the road or nearby the road. Mostly at night.

• Animals crossing streets at night.

• People walking along or standing beside a parking car, possibly opening suddenly a door.

• People standing at the back of a standing car in a traffic jam.

• Endangered motorcycles or even car during multiple lane changes - in particular on multi-lane highways.

• Children playing next to the road.

• Accidents occurring in roundabouts and in curves. Missing parameterisation of the accident by: fast or slow vulnerable user - fast or slow vehicles - traffic density rare or dense.




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• When cars are slowed by a traffic jam, PTW or bicycle overtaking vehicles from the right.

• Motor car right turning while PTW is on its right side. Motor car suddenly hardly braking while PTW is following. Motor car stopping on road side and opening door while PTW is overtaking.

• Car driver wants to get ahead of the previous car. He veers and ignores a motorcyclist behind him/her.

• Intersections where the driver attention goes in a different direction than his/her driving direction. In that case the driver looks backwards and if no cars are coming, the driver may accelerate and hit a pedestrian crossing the road in front of him/her.

• Cyclist/PTW that drives between cars in case of traffic jam.

5. Selection of Use Cases In this paragraph all elements derived from the different approaches followed to find the list of the most relevant scenarios are put together to come to the final selection and prioritisation of scenarios that are then duly described into the final cases of use. Paragraph 5.1 contains the final consideration about scenarios analysis, while paragraph 5.2 describes the WATCH-OVER relevant use cases.

5.1. Scenarios final considerations In this paragraph the selection and prioritisation effort spent in the previous sections is summarised into a final step. Among different scenarios and parameter combinations, the most relevant use cases to be addressed by the WATCH-OVER system are considered and described. The estimated frequency of scenarios occurrence and the support required from users have been gathered via questionnaire administered to 154 non expert users and they are ranked as follows.

RANKING OF THE ESTIMATED FREQUENCY

OF OCCURRENCE (SCENARIO N.)

RANKING OF THE SUPPORT REQUIRED

FROM USERS (SCENARIO N.) 1, 2 2 4 3 7 15 8, 15 10, 13 3 9, 8, 7 14, 11 11

9 14 16, 6 16, 12 5 6, 1 12, 13 5 10 4

Table 45: Ranking of scenarios gathered from questionnaire

The scenario 2 and 3 are merged as they are mirrored and from now on for simplicity this scenario will be called 2-3. The scenario 10 is removed as the estimated frequency of occurrence is the lowest as predicted by the experts. Scenario 15, as already indicated, is removed as it is addressed by lateral assistant stand alone and cooperative applications (i.e. by PReVENT and SAFESPOT projects). For this analysis the relevance for cooperative system is considered as a qualitative and not as selective parameter that indicates the real need of using a cooperative approach in different scenarios instead of a stand alone on board system based application.




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Additionally the technological feasibility is kept as a very first indication to be further explored in the next system design and development phases and not as a parameter that affects the selection of scenarios. From the previous tables (Table 39 and Table 45) the scenarios that are evaluated to be highly relevant for road safety (in terms of expected impact) and have a high estimated frequency of occurrence are: Scenario 1, 2-3 The scenarios that are evaluated to have a medium relevance for road safety and a medium estimated frequency of occurrence are: Scenario 4, 6, 7, 8, 9, 12, 13, 14, 16 The use cases will be thoroughly described for the highly relevant and highly frequent scenarios and these are the scenarios that will be specifically addressed in the design and development phase. The other scenarios will also be considered in the use cases so to be confronted in the pilot test with system performances. A final consideration is needed by comparing the results obtained so far with the methodical approach. From expert brainstorming and Table 43 the following considerations are drawn. Relevant parameters from the expert brainstorming are:

• Vehicle speed

• VRU speed

• Time to collision

• Time of day

• Weather conditions The expert brainstorming session considered the traffic density and environment and the VRU visibility as not to be considered as they are already included into the scenarios. However the methodological approach versus the brainstorming results put into evidence that the relative trajectory and the type of road are important to be considered in the use cases. Therefore the final list of parameters to be included into the use cases description is:

• Vehicle speed

• VRU speed

• Relative trajectory

• Time to collision

• Time of day

• Weather conditions

• Type of road Moreover the WATCH-OVER system is addressing scenarios that are always including a vehicle as one of the collision opponent. Therefore the Table 43 is simplified as follows:



speed


speed


D. Time of day


PCT 1 CAT-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 2 CAT-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 3 CAT-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 7 CAT-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 8 CAT-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 9 CAT-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 13 CAT-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 14 CAT-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3




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speed


speed


D. Time of day


PCT 15 CAT-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 19 CAT-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 20 CAT-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

PCT 21 CAT-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 1 CAT-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 2 CAT-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 3 CAT-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 7 CAT-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 8 CAT-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 9 CAT-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 13 CAT-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 14 CAT-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 15 CAT-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 19 CAT-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 20 CAT-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

POT 21 CAT-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 1 CAT-PTW-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 2 CAT-BIC-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 3 CAT-PED-STR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 7 CAT-PTW-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 8 CAT-BIC-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 9 CAT-PED-CUR 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 13 CAT-PTW-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 14 CAT-BIC-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 15 CAT-PED-CRO 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 19 CAT-PTW-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 20 CAT-BIC-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

RTT 21 CAT-PED-ROU 1, 2, 3 1, 2 1, 2 1, 2, 3 1, 2, 3

Table 46: Revision of Table 43 for the WATCH-OVER framework

This simplified table together with the selected scenarios represents the point of start for the description of the use cases. It has to be noted that in the time of day values dusk and dawn have been put together as light conditions are similar.

5.2. Use cases description In this paragraph the selected scenarios are described in the correlated use cases to be addressed by the WATCH-OVER system development. All relevant scenarios are now grouped by similarities. The following final tables indicate those scenarios with a high estimated occurrence and a consequent high relevance for road safety as well as those with medium occurrence.

N. DESCRIPTION SKETCH 1 Pedestrian (or cyclist)

crossing the road from the right to the left.




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N. DESCRIPTION SKETCH 2-3 Pedestrian (or cyclist)

crossing the road from the right to the left (or from the left to the right) occluded from parked or stopped cars or other obstacles.

Table 47: Group of highly relevant scenarios

These previous scenarios are those that will be directly addressed in the design and development phase of the WATCH-OVER system. The scenarios that are of medium estimated occurrence and therefore with a medium expected impact on road safety are also grouped by similarities as follows.

N. DESCRIPTION SKETCH 4 Vehicle turning left at an

intersection, pedestrian crossing the road from the right to the left (or from the left to the right).

6-9 Vehicle turning right at an

intersection, pedestrian (or cyclist) crossing the road from the right to the left (or from the left to the right).

7-8 Vehicle on a crossroad, pedal

cyclist crossing the road from the right (or from the left).




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N. DESCRIPTION SKETCH 12-14

PTW arrives from left side (or from right side) at intersection, paths perpendicular.

13 PTW arrives from left side at

intersection, paths perpendicular, occluded from parked car or other obstacles.

16 PTW (or pedal cyclist) and

vehicle travelling in opposite directions, vehicle turns in front of PTW.

Table 48: Group of medium relevant scenarios

These scenarios will also be addressed in the development of the WATCH-OVER system but they will not directly affect the definition of the system specifications. They will be taken into account in the design phase to understand from the early project stage their effective affordability with the technologies under development. These scenarios will be directly addressed in the testing phase where system performances will also be evaluated versus system applicability to these scenarios. For these reasons the use cases will also be depicted for these scenarios. Finally each selected use case is described in a specific table (from Table 50 to Table 57) where there is also the indication on how it is judged the technological feasibility (Table 49).

A High

B Medium

C Low

D Very low

Table 49: Technological feasibility marks within the WATCH-OVER framework




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An important reminder for the use case description is that the type of vehicles addressed are both the car and the truck even if in the project it is not planned to have a truck demonstrator; this is relevant to indicate that the system is applicable also to trucks. Additionally it has to be noted that case by case the motorbike can be both a vehicle and / or a vulnerable user.

CASE NAME VRU crossing the road from the right to the left

CASE ID UC1

STATUS Final

GOAL High estimated occurrence

TYPE OF VEHICLE Car, truck, motorbike

TYPE OF VRU Pedestrian, cyclist

TYPE OF ROAD Straight road

RELATIVE TRAJECTORIES Perpendicular crossing trajectories

VEHICLE SPEED Less then vehicle speed limit 10% more then vehicle speed limit 50% more then vehicle speed limit

VRU SPEED Slow (walking pedestrian, bicycle’s speed less then 25 km/h) Fast (running pedestrian, bicycle’s speed more then 25 km/h)

TIME TO COLLISION Detection time > time to collision (avoidable accident)

TIME OF THE DAY Day Dusk / Dawn Night

WEATHER Good Road slipperiness increased and/or visibility reduced but it’s still possible for the vehicle to stop before the accident with the VRU

SCENARIO DESCRIPTION STEP ACTION

1 A vehicle is driving in its own lane

2 A VRU is unexpectedly crossing the road outside the zebra stripes (or on the zebra stripes and the driver is distracted)

3 The vehicle is warned sufficiently in time to stop the vehicle before an accident occurs

OPEN ISSUES

COMMENTS Technological feasibility: A Relevance for the cooperative approach: it has to be evaluated the benefit of the cooperation of communication and sensor technologies versus stand alone systems

Table 50: Use case 1 description




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CASE NAME VRU crossing the road from the right to the left occluded from parked or

stopped cars or other obstacles

CASE ID UC2

STATUS Final

GOAL High estimated occurrence



TYPE OF ROAD Straight road


VEHICLE SPEED Less then vehicle speed limit 10% more then vehicle speed limit 50% more then vehicle speed limit






1 A vehicle is driving in its own lane

2 A VRU is unexpectedly crossing the road outside the zebra stripes (or on the zebra stripes and the driver is distracted) coming out from behind a parked car or another occluding obstacle

3 The vehicle is warned sufficiently in time to stop the vehicle before an accident occurs

OPEN ISSUES

COMMENTS Technological feasibility: A





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CASE NAME Vehicle turning left at an intersection (*), pedestrian crossing the road from the right to the left (or from the left to the right)

CASE ID UC3

STATUS Final

GOAL Medium estimated occurrence


TYPE OF VRU Pedestrian

TYPE OF ROAD Crossing

RELATIVE TRAJECTORIES Respective turning trajectories

VEHICLE SPEED Less then vehicle speed limit 10% more then vehicle speed limit

VRU SPEED Slow (walking pedestrian) Fast (running pedestrian)

TIME TO COLLISION Detection time > time to collision (avoidable accident) Detection time < time to collision (unavoidable accident; severity can be reduced)




1 A vehicle is driving in its own lane and is turning left at an intersection

2 A pedestrian is unexpectedly crossing the road outside the zebra stripes (or on the zebra stripes and the driver is distracted)

3 The vehicle is warned sufficiently in time to stop the vehicle before an accident occurs or it is warned in time only to reduce accident severity

OPEN ISSUES

COMMENTS Technological feasibility: B

(*) for right hand driving countries this scenario has to be mirrored





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CASE NAME Vehicle turning right (*) at an intersection, VRU crossing the road from the right to the left (or from the left to the right)

CASE ID UC4

STATUS Final












1 A vehicle is driving in its own lane and is turning right at an intersection

2 A VRU is unexpectedly crossing the road outside the zebra stripes (or on the zebra stripes and the driver is distracted)


OPEN ISSUES

COMMENTS Technological feasibility: C This scenario is very difficult to address as the video sensor technology cannot offer support and the communication technology should include precise localisation






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CASE NAME Vehicle at a crossroad, pedal cyclist crossing the road from the right (or from the left)

CASE ID UC5

STATUS Final



TYPE OF VRU Cyclist




VRU SPEED Slow (bicycle’s speed less then 25 km/h) Fast (bicycle’s speed more then 25 km/h)





1 A bicyclist is entering a crossing with right to go

2 The vehicle is entering the crossing without seeing the bicyclist


OPEN ISSUES






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CASE NAME PTW arrives from left side (or from right side) into vehicle at intersection, paths perpendicular

CASE ID UC6

STATUS Final


TYPE OF VEHICLE Car, truck

TYPE OF VRU PTW




VRU SPEED Less then vehicle speed limit 10% more then vehicle speed limit 50% more then vehicle speed limit





1 A PTW is entering a crossing with right to go

2 The vehicle is accessing the crossing without seeing the PTW

3 The vehicle and / or the PTW are warned sufficiently in time to stop before an accident occurs or they are warned in time only to reduce accident severity

OPEN ISSUES

COMMENTS Technological feasibility: C





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CASE NAME PTW arrives from left side at intersection (*), paths perpendicular, occluded from parked car or other obstacles

CASE ID UC7

STATUS Final



TYPE OF VRU PTW




VRU SPEED Less then vehicle speed limit 10% more then vehicle speed limit 50% more then vehicle speed limit





1 A PTW is entering a crossing with right to go

2 The vehicle is accessing the intersection without seeing the PTW


OPEN ISSUES

COMMENTS Technological feasibility: C






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CASE NAME PTW (or pedal cyclist) and vehicle travelling in opposite directions, vehicle turns in front of PTW

CASE ID UC8

STATUS Final



TYPE OF VRU Cyclist, PTW



VEHICLE SPEED Less then vehicle speed limit 10% more then vehicle speed limit 50% more then vehicle speed limit for a PTW

VRU SPEED Slow (bicycle’s speed less then 25 km/h) or Fast (bicycle’s speed more then 25 km/h) for a pedal cyclist. Less then vehicle speed limit; 10% more then vehicle speed limit and 50% more then vehicle speed limit for a PTW





1 A VRU is entering a crossing with right to go

2 The vehicle is turning left in front of the VRU without seeing him, or without properly evaluating respective velocities


OPEN ISSUES






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Conclusions The design of the WATCH-OVER system should be based on a solid understanding of the relevant use cases in which the system is conceived to be used and on users’ requirements. For this reason the selection of the scenarios and use cases should be done as thoroughly as possible. Therefore experts involved in these tasks, that are part of the “WP2 – User requirements and scenarios” decided to go for a multiple approach (with a cross confrontation and verification of the results) that should guarantee, in this specific case in which the relevant use cases should be defined a priori, more trustable results in respect to a single-method approach. This documents reports:

• preliminary information on accidents analysis derived from predecessor projects (PROTECTOR, SAVE-U, MAIDS);

• the relevant scenarios for the WATCH-OVER application derived from the analysis of the accident databases that have been found available, recent and relevant in Europe with a complement (especially where not available in Europe) in the USA;

• the analysis of the scenarios performed by experts that enabled the identification of additional relevant scenarios, the parameterisation of scenarios, the a priori rough evaluation of their feasibility with the proposed technologies and their relevance in respect to the cooperative approach;

• the scenarios emerged after the expert brainstorming analysis have been submitted to an extended user questionnaire administration (to more than 150 users) that enabled the collection of relevant parameters to refine the prioritisation of the scenarios and the collection of useful user requirements;

• the final ranking of the relevant scenarios and the related use cases description. It has to be noted that the selection of the different approaches as well as of the methodologies followed in this task are not the only possible paths that could be followed, however the team involved in these activities believes that the results obtained via the proposed multiple approach are remarkable for the prosecution of the WATCH-OVER activities, namely for the definition of the system functionality and specifications.




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References

BAST, Verkehrsunfälle 1998, Fachserie 8, Reihe 7.

BAST, Verkehrsunfälle 2000, Fachserie 8, Reihe 7.

Berg, A., J. Dettinger and J. Grandel, Personenkraftwagen / Fußgänger-Unfälle - Erkenntnisse aus

neueren Untersuchungen und Crash-Tests mit besonderer Berücksichtigung moderner

Kompaktfahrzeuge, Verkehrsunfall und Fahrzeugtechnik, Heft 9, September 1997.

Boyer, S., C. Decamme, M. Hourdebaigt and O. Noel, La sécurité des piétons en 1995: Etude

sectorielle, Observatoire National Interministériel de la Sécurité routière, ISBN 2-11-003686-9.

ETSC, Transport safety performance in the EU, A statistical overview, European Transport Safety

Council, Brussels, 2003.

MAIDS project Final Report, In-depth investigations of accidents involving powered two-wheelers,

2004.

Otte D. and E. G. Suren, Der Fahrradunfall – Eine verkehrsmedizinischtechnisch Analyse, 1985.

PROTECTOR project Deliverable N. D02.2/D02.3, User Needs Investigation Results. Critical

scenarios which will benefit from PROTECTOR, September 2000.

SAFETYNET project Deliverable N. 1, Annual Statistical Report 2004, based on data from the

CARE database, 2005.

SAVE-U project Deliverable N. 1A, Vulnerable Road User Scenario Analysis, February 2003.

Stanzel, M., M.-M. Meinecke and M.A. Obojski, Statistical Analysis of German In-Depth Accident

Study (GIDAS), April 2002.

Volvo Trucks Corporation Accident Research Team, Traffic Accidents Involving Heavy Trucks

Causing Serious to Fatal Injuries (Sweden/Europe), Rating 1, Publication

vtcart_typeaccidents_040415.xls, VTC ART, 2004.

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