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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.
Since 2005 the German In-Depth Accident Study (GIDAS) also records aspects of active vehicle safety. This is done because vehicles are fitted with an increasing number of active safety devices which have undoubtedly an influence on the number, severity and course of accidents. Accident researchers expect that collecting active safety data will facilitate to assess and quantify the impact of these and future devices. It is the aim of this paper to outline benefits and limitations associated with the recording of active safety aspects within indepth studies. An overview about possible areas where active safety data can be useful will be given. For that purpose single safety or comfort systems will be selected to estimate the effects of an accident database which includes variables associated with these systems. Questions with regard to the limitations of collecting active safety data will be addressed. Possible items are for example the usability of the data recorded, the real accident cause, the small number of relevant accidents, the time span needed to gather a sufficient dataset, the small share of vehicles equipped with a certain system or different functionalities of systems that are supposed to fall in the same category. As a result user needs for a reasonable data collection of active safety elements will be elaborated.