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Evaluation of Drivers Interaction with Assistant Systems Using Criticality Driven Guided Simulation

机译:使用关键驱动的引导仿真评估驾驶员与辅助系统的交互

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摘要

Advanced Driver Assistance Systems (ADAS) operate more and more autonomously and take over essential parts of the driving task e.g. keeping safe distance or detecting hazards. Thereby they change the structure of the driver's task and thus induce a change in driver's behavior. Nevertheless it is still the driver who is ultimately responsible for the safe operation of the vehicle. Therefore it is necessary to ensure that the behavioral changes neither reduce the controllability of the vehicle nor the controllability of the hazardous events. We introduce the Threshold Uncertainty Tree Search (TUTS) algorithm as a simulation based approach to explore rare but critical driver behavior in interaction with an assistance system. We present first results obtained with a validated driver model in a simple driving scenario.
机译:高级驾驶员辅助系统(ADAS)越来越多地自主运行,并接管了驾驶任务的重要部分,例如保持安全距离或发现危险。因此,它们改变了驾驶员任务的结构,从而引起了驾驶员行为的改变。尽管如此,最终还是要由驾驶员来保证车辆的安全运行。因此,必须确保行为改变既不会降低车辆的可控制性,也不会降低危险事件的可控制性。我们引入阈值不确定性树搜索(TUTS)算法作为基于仿真的方法,以探索与辅助系统交互时稀有但关键的驾驶员行为。我们介绍了在简单的驾驶场景中使用经过验证的驾驶员模型获得的第一个结果。

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