Predicting vehicle trajectory accurately is a crucial task for an autonomous vehicle. It is also necessary for many Advanced Driver Assistance System to predict trajectory of the ego-vehicle’s. In recent years, some vehicles trajectory prediction algorithm is mainly based on a simple Motion Model. This paper puts forward a method which combines road recognition and the hypothesis of steady preview and dynamic correction for trajectory prediction. In the road recognition algorithm, both methods of Kalman Filter (KF) and Recursive Least-Square (RLS) work well to estimate the road slope and road friction coefficient.


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    Titel :

    Vehicle Trajectory Prediction Based on Road Recognition



    Erschienen in:

    Erscheinungsdatum :

    2014-08-11


    Format / Umfang :

    7 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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