In this paper, we address the application of stochastic model predictive control with chance constraints to autonomous driving. We use a condensed formulation of a linearized vehicle model to setup a quadratic program with nonlinear chance constraints, which can be solved with off-the-shelf optimization algorithms. We further show how obstacle information in the path planning stage can be converted into a set of linear state constraints that can be directly used in the control algorithm. The resulting controller is potentially real-time capable and achieves a tradeoff between safety and comfort in its control behavior.


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    Titel :

    Stochastic model predictive controller with chance constraints for comfortable and safe driving behavior of autonomous vehicles


    Beteiligte:
    Lenz, David (Autor:in) / Kessler, Tobias (Autor:in) / Knoll, Alois (Autor:in)


    Erscheinungsdatum :

    01.06.2015


    Format / Umfang :

    695269 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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