Focusing on autonomous driving algorithm development, this paper proposes a novel real-time trajectory planner formulated as a Nonlinear Model Predictive Control (NMPC) algorithm. The mathematical formulation of the problem is deeply reported and discussed. The numerical solution of the NMPC problem is the result of a novel genetic algorithm strategy that represents the innovative aspect of the work proposed. The aim of this paper is also to show how genetic algorithm can be a valid approach for motion planning strategies. Numerical results are discussed through simulations that show a reasonable behaviour of the proposed strategy in the presence of moving obstacles as well as in a wide range of road friction conditions. Moreover, a real-time implementation for research purposes is assumed as possible by considering computational time analysis reported.


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    Titel :

    MPC trajectory planner for autonomous driving solved by genetic algorithm technique


    Beteiligte:
    Arrigoni, S. (Autor:in) / Braghin, F. (Autor:in) / Cheli, F. (Autor:in)

    Erschienen in:

    Vehicle System Dynamics ; 60 , 12 ; 4118-4143


    Erscheinungsdatum :

    02.12.2022


    Format / Umfang :

    26 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Unbekannt




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