Traditional driving behavior researches mainly focus on the identification of drivers' bad driving behaviors. However, the traditional method is hardly competent for quantitatively measuring the degree of driving behaviors' risks, and it is not qualified for supporting value-added services based on the assessment of driving behaviors, such as vehicle insurance service. Through analysis of the vehicle travel state information such as steering wheel angle signal, brake pedal signal, and so forth, which are collected by the multi-sensor equipped on vehicles, this paper established a correlation method between vehicle status information and driver's different driving behaviors. Furthermore, this paper proposed a driving behavior tendency degree measure method based on vehicle status information by means of multi-index Analytic Hierarchy Process (AHP) and fulfills the construction of the fusion decision model about the degree of the driving behaviors by means of BP neural network. Finally, the outputs are mapped to a radar chart which enables the risk degree of different driving behaviors to be presented straightforwardly. Verified by driving data, the method provides a better comprehensive assessment of the risk of driving behaviors.


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    Titel :

    A Study on Driving Behavior Risk Assessment Method with Multi-Sensor Information


    Beteiligte:
    Ning, Fuxuan (Autor:in) / Li, Jinglin (Autor:in) / Sun, Qibo (Autor:in)

    Kongress:

    Second International Conference on Transportation Information and Safety ; 2013 ; Wuhan, China


    Erschienen in:

    ICTIS 2013 ; 1426-1431


    Erscheinungsdatum :

    2013-06-11




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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