Concerning the market introduction of automated driving, one of the major challenges for many years to come is to identify risks and benefits of these functions. Since automated driving functions are addressing a huge amount of relevant driving situations by means of their complex decision making algorithms, their effectiveness has to be determined in all possible driving situations in their operational design domain. Besides, the automated driving functions need to be assessed with respect to human driving performance according to the guidelines defined by the German Ethics Commission for Automated and Connected Driving [1]. Thus, based on a methodology for safety performance assessment of automated driving functions, this paper introduces specific driver models for modelling of human driver performance. How these models have to be structured and parameterized in order to present the variety of human driver performance under different situational variations is investigated in this paper. For validation of the derived models, a study in a highly dynamic driving simulator on the example of a near-crash cut-in driving situation was carried out.
Modelling Human Driver Performance for Safety Assessment of Road Vehicle Automation
2018-11-01
1194271 byte
Conference paper
Electronic Resource
English
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