Forward Collision Warning (FCW) is an advanced driver assistance system (ADAS) designed to prevent or reduce the severity of a collision by providing early warnings to the driver. The core algorithm of a FCW-system is based on the distance between the vehicle and the obstacle as a warning threshold. Since the system assumes a particular reaction time for all drivers, the threshold value cannot be individualized for different driver states and thus leads to false or unnecessary alarms. Therefore, this paper proposes an adaptive custom collision warning system. The system relies on camera images to collect data like age, emotion, fatigue, and attention of the driver through Deep Residual Networks and the PERCLOS-method (Percentage eye openness tracking). The information obtained is evaluated using fuzzy logic and an appropriate reaction time is derived. The improved safe-distance algorithm calculates a safety distance appropriate to the driver’s condition. The system is evaluated with the National Highway Traffic Safety Administration (NHTSA) FCW standard test through the simulation environment IPG CarMaker.


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    Titel :

    Adaptive Customized Forward Collision Warning System Through Driver Monitoring


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Arai, Kohei (Herausgeber:in) / Kapoor, Supriya (Herausgeber:in) / Bhatia, Rahul (Herausgeber:in) / Stang, Marco (Autor:in) / Sommer, Martin (Autor:in) / Baumann, Daniel (Autor:in) / Zijia, Yuan (Autor:in) / Sax, Eric (Autor:in)

    Kongress:

    Proceedings of the Future Technologies Conference ; 2020 ; San Francisco, CA, USA November 05, 2020 - November 06, 2020



    Erscheinungsdatum :

    2020-11-01


    Format / Umfang :

    16 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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