This paper presents a methodology and mobile application for driver monitoring, analysis, and recommendations based on detected unsafe driving behavior for accident prevention using a personal smartphone. For the driver behavior monitoring, the smartphone’s cameras and built-in sensors (accelerometer, gyroscope, GPS, and microphone) are used. A developed methodology includes dangerous state classification, dangerous state detection, and a reference model. The methodology supports the following driver’s online dangerous states: distraction and drowsiness as well as an offline dangerous state related to a high pulse rate. We implemented the system for Android smartphones and evaluated it with ten volunteers.


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    Titel :

    Methodology and Mobile Application for Driver Behavior Analysis and Accident Prevention


    Beteiligte:
    Kashevnik, Alexey (Autor:in) / Lashkov, Igor (Autor:in) / Gurtov, Andrei (Autor:in)


    Erscheinungsdatum :

    2020-06-01


    Format / Umfang :

    3431264 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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