In this study, a driver model with the multiple regression and the neural network is constructed to analyze the relationship between the driver's control action and the information that includes data of vehicle behavior and environment. Using these models, effectiveness of the information to control the action of a driver is examined. To evaluate the intelligent driver support systems, Mental Work Load (MWL) model is constructed with the multiple regression and the neural network. MWL is expressed as Heart Rate Variability (HRV). Measured HRV data and calculated HRV data with MWL model show good agreement. Effectiveness of information is examined using the MWL model. From these results, it is shown that the analytical method with the driver's MWL can be used to assess and improve the intelligent driver support systems as the next stage of this research.


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    Titel :

    A research on analytical method of driver-vehicle-environment system for construction of intelligent driver support system


    Beteiligte:
    Kuriyagawa, Y. (Autor:in) / Im, Hyung-Eun (Autor:in) / Kageyama, I. (Autor:in) / Onishi, S. (Autor:in)

    Erschienen in:

    Vehicle System Dynamics ; 37 , 5 ; 339-358


    Erscheinungsdatum :

    2002


    Format / Umfang :

    20 Seiten, 15 Quellen




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Print


    Sprache :

    Englisch






    A Research on Analytical Method of Driver-Vehicle-Environment System for Construction of Intelligent Driver Support System

    Kuriyagawa, Yukiyo / Im, Hyung-Eun / Kageyama, Ichiro et al. | Taylor & Francis Verlag | 2002


    Intelligent Driver Support

    Tribe, R. / Prynne, K. / Westwood, I. et al. | British Library Online Contents | 1997


    Intelligent Driver Support

    Tribe, R. / Prynne, K. / Westwood, I. et al. | British Library Conference Proceedings | 1995