Refine
Keywords
- Radfahrer (2)
- Accident (1)
- Active safety system (1)
- Aktives Sicherheitssystem (1)
- Analyse (math) (1)
- Analysis (math) (1)
- Bicyclist (1)
- Collision (1)
- Cyclist (1)
- Driver assistance system (1)
Institute
- Sonstige (2) (remove)
The presence and performance of Advanced Driver Assistance Systems (ADAS) has increased over last years. Systems available on the market address also conflicts with vulnerable road users (VRUs) such as pedestrians and cyclists. Within the European project PROSPECT (Horizon2020, funded by the EC) improved VRU ADAS systems are developed and tested. However, before determining systems" properties and starting testing, an up-to-date analysis of VRU crashes was needed in order to derive the most important Use Cases (detailed crash descriptions) the systems should address. Besides the identified Accident Scenarios (basic crash descriptions), this paper describes in short the method of deriving the Use Cases for car-to-cyclist crashes. Method Crashes involving one passenger car and one cyclist were investigated in several European crash databases looking for all injury severity levels (slight, severe and fatal). These data sources included European statistics from CARE, data on national level from Germany, Sweden and Hungary as well as detailed accident information from these three countries using GIDAS, the Volvo Cars Cyclist Accident database and Hungarian in-depth accident data, respectively. The most frequent accident scenarios were studied and Use Cases were derived considering the key aspects of these crash situations (e.g., view orientation of the cyclist and the car driver- manoeuvre intention) and thus, form an appropriate basis for the development of Test Scenarios. Results Latest information on car-to-cyclist crashes in Europe was compiled including details on the related crash configurations, driving directions, outcome in terms of injury severity, accident location, other environmental aspects and driver responsibilities. The majority of car-to-cyclist crashes occurred during daylight and in clear weather conditions. Car-to-cyclist crashes in which the vehicle was traveling straight and the cyclist is moving in line with the traffic were found to result in the greatest number of fatalities. Considering also slightly and seriously injured cyclists led to a different order of crash patterns according to the three considered European countries. Finally the paper introduced the Use Cases derived from the crash data analysis. A total of 29 Use Cases were derived considering the group of seriously or fatally injured cyclists and 35 Use Cases were derived considering the group of slightly, seriously or fatally injured cyclists. The highest ranked Use Case describes the collision between a car turning to the nearside and a cyclist riding on a bicycle lane against the usual driving direction. A unified European dataset on car-to-cyclist crash scenarios is not available as the data available in CARE is limited, hence national datasets had to be used for the study and further work will be required to extrapolate the results to a European level. Due to the large number of Use Cases, the paper shows only highest ranked ones.
PROSPECT (Proactive Safety for Pedestrians and Cyclists) is a collaborative research project involving most of the relevant partners from the automotive industry (including important active safety vehicle manufacturers and tier-1 suppliers) as well as academia and independent test labs, funded by the European Commission in the Horizon 2020 research program. PROSPECT's primary goal is the development of novel active safety functions, to be finally demonstrated to the public in three prototype vehicles. A sound benefit assessment of the prototype vehicle's functionality requires a broad testing methodology which goes beyond what has currently been used. Since PROSPECT functions are developed to prevent accidents in intersections, a key aspect of the test methodology is the reproduction of natural driving styles on the test track with driving robots. For this task, data from a real driving study with subjects in a suburb of Munich, Germany was used. Further data from Barcelona will be available soon. The data suggests that intersection crossing can be broken down into five phases, two phases with straight deceleration / acceleration, one phase with constant radius and speed turning, and two phases where the bend is imitated or ended. In these latter phases, drivers mostly combine lateral and longitudinal accelerations and drive what is called a clothoid, a curve with curvature proportional to distance travelled, in order to change lateral acceleration smoothly rather than abrupt. The data suggests that the main parameter of the clothoid, the ratio distance travelled to curvature, is mostly constant during the intersections. This parameter together with decelerations and speeds allows the generation of synthetic robot program files for a reproduction of natural driving styles using robots, allowing a much greater reproducibility than what is possible with human test drivers. First tests show that in principle it is possible to use the driving robots for vehicle control in that manner; a challenge currently is the control performance of the robot system in terms of speed control, but it is anticipated that this problem will be solved soon. Further elements of the PROSPECT test methodology are a standard intersection marking to be implemented on the test track which allows the efficient testing of all PROSPECT test cases, standard mobile and light obstruction elements for quick reproduction of obstructions of view, and a concept for tests in realistic surroundings. First tests using the PROSPECT test methodology will be conducted over the summer 2017, and final tests of the prototype vehicles developed within PROSPECT will be conducted in early 2018