It is apparent that one cannot rely solely on physical test drives for ensuring the correct functionality of autonomous vehicles. Since physical test drives are costly and time consuming, it is advantageous to accompany them with computer simulations. However, since most traffic scenarios are not challenging, even simulations are often too time consuming. To address this issue, we present an approach that creates automatically critical driving situations, i.e., situations with a small solution space for avoiding a collision. Our approach combines reachability analysis for determining the size of the solution space with optimization techniques to shrink it. The solution space is reduced by shifting the initial states of traffic participants, demanding an immediate and correct action of the vehicle under test. We demonstrate our approach by automatically increasing the criticality of several initially uncritical situations recorded from real traffic.


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    Titel :

    Automatic Generation of Safety-Critical Test Scenarios for Collision Avoidance of Road Vehicles


    Beteiligte:


    Erscheinungsdatum :

    2018-06-01


    Format / Umfang :

    1510833 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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