Efficient trajectory planning plays a crucial role in the development of autonomous vehicles, ensuring safe and optimized navigation in dynamic environments. This paper proposes a novel energy-efficient hybrid trajectory planning by integrating a sampling-based method with an optimization-based path refining method. It uses the strength of the sampling-based methods to reduce the solution space and generate a reactive trajectory in a dynamic environment. Following path selection, a septic path is generated and utilized as a reference for an energy-efficient path-refining optimization problem, producing a jerk-controlled trajectory with enhanced computational efficiency. The simulations were conducted in a joint-simulation environment using Simulink/Matlab and the Scaner Studio vehicle dynamics and driving environment simulator. The findings demonstrate the effectiveness of our approach in achieving significant energy savings while adeptly addressing dynamically changing environments.


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    Titel :

    Hybrid Energy-Efficient Local Path Planning for Autonomous Vehicles in Dynamic Environments


    Beteiligte:
    Tarhini, Fadel (Autor:in) / Talj, Reine (Autor:in) / Doumiati, Moustapha (Autor:in)


    Erscheinungsdatum :

    24.09.2024


    Format / Umfang :

    1841227 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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