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Advancing active safety towards the protection of vulnerable road users: the PROSPECT project
(2017)
Accidents involving Vulnerable Road Users (VRU) are still a very significant issue for road safety. According to the World Health Organisation, pedestrian and cyclist deaths account for more than 25% of all road traffic deaths worldwide. Autonomous Emergency Braking Systems have the potential to improve safety for these VRU groups. The PROSPECT project (Proactive Safety for Pedestrians and Cyclists) aims to significantly improve the effectiveness of active VRU safety systems compared to those currently on the market by expanding the scope of scenarios addressed by the systems and improving the overall system performance. The project pursues an integrated approach: Newest available accident data combined with naturalistic observations and HMI guidelines represent key inputs for the system specifications, which form the basis for the system development. For system development, two main aspects are considered: advanced sensor processing with situation analysis, and intervention strategies including braking and steering. All these concepts are implemented in several vehicle prototypes. Special emphasis is put on balancing system performance in critical scenarios and avoiding undesired system activations. For system validation, testing in realistic scenarios will be done. Results will allow the performance assessment of the developed concepts and a cost-benefit analysis. The findings within the PROSPECT project will contribute to the generation of state -of-the-art knowledge, technical innovations, assessment methodologies and tools for advancing Advanced Driver Assistance Systems towards the protection of VRUs. The introduction of a new generation safety system in the market will enhance VRU road safety in 2020-2025, contributing to the "Vision Zero" objective of no fatalities or serious injuries in road traffic set out in the Transport White Paper. Furthermore, the test methodologies and tools developed within the project shall be considered for the New Car Assessment Programme (Euro NCAP) future roadmaps, supporting the European Commission goal of halving the road toll in the 2011-2020 timeframe.
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.
For more than a decade, ADAC accident researchers have analysed road accidents with severe injuries, recording some 20,000 accidents. An important task in accident research is to determine the causative factors of road accidents. Apart from vehicle engineering and human factors, accident research also focuses on infrastructural and environmental aspects. To find out what accident scenarios are the most common in ADAC accident research and what driver assistance systems can prevent them, our first task was to conduct a detailed accident analysis. Using CarMaker, we performed a realistic simulation of accident scenarios, including crashes, with varying parameters. To begin with, we made an initial selection of driver assistance systems in order to determine those with the greatest accident prevention potential. One important finding of this study is that the safety potential of the individual driver assistance systems can actually be examined. It also turned out that active safety offers even much more potential for development and innovation than passive safety. At the same time, testing becomes more demanding, too, as new systems keep entering the market, many of them differing in functional details. ADAC will continue to test all driver assistance systems as realistically as possible so as to be able to provide advice to car buyers. Therefore, it will be essential to develop and improve test conditions and criteria.
Assessment of the effectiveness of Intersection Assistance Systems at urban and rural accident sites
(2015)
An Intersection Collision Avoidance System is a promising safety system for accident avoidance or injury mitigation at junctions. However, there is still a lack of evidence of the effectiveness, due to the missing real accident data concerning Advanced Driver Assistance Systems. The objective of this study is the assessment of the effectiveness of an Intersection Collision Avoidance System based on real accidents. The method used is called virtual pre-crash simulation. Accidents at junctions were reconstructed by using the numerical simulation software PC-Crashâ„¢. This first simulation is called the baseline simulation. In a second step the vehicles of these accidents were equipped with an Intersection Collision Avoidance System and simulated again. The second simulation is called the system simulation. In the system simulation two different sensors and four different intervention strategies were used, based on a time-to-collision approach. The effectiveness of Intersection Collision Avoidance System has been evaluated by using an assessment function. On average 9% of the reviewed junction accidents could have been avoided within the system simulations. The other simulation results clearly showed a change in the principal direction of force, delta-v and reduction of the injury severity.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
The Traffic Accident Research Institute at University of Technology Dresden investigates about 1,000 accidents annually in the area around and in Dresden. These datasets have been summarized and evaluated in the GIDAS (German Accident In-Depth Study) project for 13 years. During the project it became apparent that the specific traffic situation of a covert exit of a passenger car and an intersecting two-wheeler involves a high risk potential. This critical situation develops in a large part due to the lack of visibility between the driver and the intersecting bike. In this paper the accident avoidance potential of front camera systems with lateral field of view, which allows the driver to have an indirect sight into the crossing street area will be presented.
For the estimation of the benefit and effect of innovative Driver Assistance Systems (DAS) on the collision positions and by association on the accident severity, together with the economic benefit, it becomes necessary to simulate and evaluate a variety of virtual accidents with different start values (e.g. initial speed). Taken into account the effort necessary for a manual reconstruction, only an automated crash computation can be considered for this task. This paper explains the development of an automated crash computation based on GIDAS. The focus will be on the design of the virtual vehicle models, the method of the crash computation as well as exemplary applications of the automated crash computation. For the first time an automated crash computation of passenger car accidents has been realized. Using the automated crash computation different tasks within the field of vehicle safety can be elaborated. This includes, for example, the calculation of specific accident parameters (such as EES or delta-V) for various accident constellations and the estimation of the economic benefit of DAS using IRFs (Injury Risk Functions).
The project UR:BAN "Cognitive assistance (KA)" aims at developing future assistance systems providing improved performance in complex city traffic. New state-of-the-art panoramic sensor technologies now allow comprehensive monitoring and evaluation of the vehicle environment. In order to improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is the evaluation and prediction of their behaviour and actions. The objective of subproject "WER" is development support by providing quantitative estimates of traffic collisions at the very start and predict potential in terms of optimized accident avoidance and reduction of injury severity. For this purpose an integrated computer simulation toolkit is being devised based on real world accidents (GIDAS as well as video documented accidents), allowing the prediction of potential effectiveness and future benefit of assistance systems in this accident scenario. Subsequently, this toolkit may be used for optimizing the design of implemented assistance systems for improved effectiveness.
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.
The Swedish National Road Administration (SNRA), the Japanese Automobile Research Institute (JARI) and the Federal Highway Research Institute (BASt) are co-operating in the International Harmonized Research Activities on Intelligent Transportation Systems (IHRA-ITS). Under this umbrella a joint study was conducted. The overall objective of this study was to contribute to the definition and validation of a "battery of tools" which enables a prediction and an assessment of changes in driver workload due to the use of in-vehicle information systems (IVIS) while driving. In this sense \"validation\" means to produce empirical evidence from which it can be concluded that these methods reliably discriminate between IVIS which differ in terms of relevant features of the HMI-design. Additionally these methods should also be sensitive to the task demands imposed on the driver by the traffic situation and their interactions with HMI-design. To achieve these goals experimental validation studies (on-road and in the simulator) were performed in Sweden, Germany and Japan. As a common element these studies focused on the secondary task methodology as an approach to the study of driver workload. In a joint German-Swedish on-road study the Peripheral Detection Task (PDT) was assessed with respect to its sensitivity to the complexity of traffic situations and effects of different types of navigation systems. Results show that the PDT performance of both the German and the Swedish subjects reflects the task demands of the traffic situations better than those of the IVIS. However, alternative explanations are possible which will be examined by further analyses. Results of this study are supplemented by the Japanese study where informational demands induced by various traffic situations were analysed by using a simple arithmetic task as a secondary task. Results of this study show that relatively large task demands can be expected even from simple traffic situations.