Advanced driver assistance and automated driving can influence traffic safety in a variety of ways. Development and implementation of safety-relevant functions require prospective, quantitative assessment of their traffic safety impacts. Both benefits and risks can be quantified using simulation-based virtual experimental techniques. To this end, traffic phenomena are modeled taking into account key safety-relevant processes and "stochastic" simulation is performed on large, representative virtual samples. The virtual representations of traffic phenomena are based on detailed, stochastic models of drivers, vehicles, traffic flow, and the road environment, together with their interactions. The models incorporate knowledge from FOT, NDS, laboratory and driving simulator experiments, and other sources. Large-scale, comprehensive simulations could help in identifying and evaluating the relevant situations in which automated driving impacts traffic safety. The goal is a standardized harmonized methodology, agreed upon by all stakeholders, for holistic assessment of the impact of new driver assistance or automatic driving functions on traffic safety.


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    Titel :

    Safety Performance Assessment of Assisted and Automated Driving by Virtual Experiments: Stochastic Microscopic Traffic Simulation as Knowledge Synthesis


    Beteiligte:
    Helmer, Thomas (Autor:in) / Wang, Lei (Autor:in) / Kompass, Klaus (Autor:in) / Kates, Ronald (Autor:in)


    Erscheinungsdatum :

    01.09.2015


    Format / Umfang :

    168157 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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