The contribution at hand combines a sampling-based trajectory planning approach and a model predictive trajectory tracking controller to a collision avoidance system. The planner generates candidate trajectories by the suitable selection of breakpoints which are connected by a spline interpolation. A procedure is presented to systematically select sample states to perform a collision avoidance maneuver in case of an emergency situation. The vehicle is controlled to the optimal trajectory of the planner by comparison with a model predictive trajectory set. This is determined by the prediction of a detailed nonlinear vehicle model for constant input variables. A suitable objective function with a time weighting is utilized to evaluate the individual trajectories and to select the optimal input variables.


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    Titel :

    Sampling-based Trajectory Planning and Control for a Collision Avoidance System


    Beteiligte:
    Homann, Andreas (Autor:in) / Lienke, Christian (Autor:in) / Keller, Martin (Autor:in) / Buss, Markus (Autor:in) / Mohamed, Manoj (Autor:in) / Bertram, Torsten (Autor:in)


    Erscheinungsdatum :

    01.10.2019


    Format / Umfang :

    436603 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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