This paper presents a novel personalized driver assistance system(PDAS) based on the model predictive control(MPC) together with a continuous/discrete hybrid dynamical system model of the driving behavior. First of all, the driving behavior is identified as the piecewise ARX model. Then, it is explicitly embedded in the optimization problem for finding the optimal assisting output. Since the driving behavior includes some binary variables, the optimization problem is formulated as the mixed integer programming. Some adaptation mechanism to accommodate to the change of the situation is particularly discussed. Finally, the proposed scheme is tested by using the real vehicle wherein the real-time assisting control based on MPC is implemented.


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    Titel :

    An experimental study on longitudinal driving assistance based on model predictive control


    Beteiligte:
    Okuda, Hiroyuki (Autor:in) / Tazaki, Yuichi (Autor:in) / Suzuki, Tatsuya (Autor:in)


    Erscheinungsdatum :

    01.06.2013


    Format / Umfang :

    3131764 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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    Okuda, H. / Tazaki, Y. / Suzuki, T. et al. | British Library Conference Proceedings | 2013


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