In future mixed traffic Highly Automated Vehicles (HAV) will have to resolve interactions with human operated traffic. A particular problem for HAVs is detection of human states influencing safety critical decisions and driving behavior of humans. We demonstrate the value proposition of neurophysiological sensors and driver models for optimizing performance of HAVs under safety constraints in mixed traffic applications.


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    Titel :

    Integrating Neurophysiological Sensors and Driver Models for Safe and Performant Automated Vehicle Control in Mixed Traffic*


    Beteiligte:
    Damm, W. (Autor:in) / Franzle, M. (Autor:in) / Ludtke, A. (Autor:in) / Rieger, J. W. (Autor:in) / Trende, A. (Autor:in) / Unni, A. (Autor:in)


    Erscheinungsdatum :

    2019-06-01


    Format / Umfang :

    534154 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    INTEGRATING NEUROPHYSIOLOGICAL SENSORS AND DRIVER MODELS FOR SAFE AND PERFORMANT AUTOMATED VEHICLE CONTROL IN MIXED TRAFFIC*

    Damm, W. / Fränzle, M. / Lüdtke, A. et al. | British Library Conference Proceedings | 2019


    Neurophysiological Driver Behavior Analysis

    Kamaruddin, Norhaslinda / Wahab, Abdul / Alarabi, K. F. et al. | TIBKAT | 2020