Karl-Heinz Siedersberger

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Advanced Driver Assistance Systems (ADAS) require an understanding of complex traffic situations. Such complexity can be handled by decomposing traffic situations into analyzeable subsets called Situation Aspects (SA). Since lots of situation analyzing problems result in classification tasks, the Scenario Based Random Forest (SBRF) algorithm is introduced(More)
As drivers back out of the driving task, when transported automatically by an intelligent car for a longer time, they are not always able to react properly, if a driver take over request occurs. This paper presents two ways, how to deal with this problem within the scope of a functional safety concept. Thereto, the difference between fully automatic and(More)
Driver inattention is reported to be one of the most prominent contributing factors to crashes. Modern vehicles feature sensor equipment able to detect an imminent collision, potentially permitting advanced driver assistance systems (ADAS) to cope for such human error. Steering interventions, however, make high demands on the human-machine-interaction.(More)
Combining real driving experience with the safety and replicability of a simulation, the Vehicle in the Loop (VIL) setup potentially qualifies as an ideal tool for the development and evaluation of safety-related driver assistance systems. Previous studies have assessed this high-fidelity simulator's validity for longitudinal driving behavior. Aiming to(More)
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