Safe and human-like path planning in urban environments remain one of the most challenging problems for autonomous driving. This paper proposes a solution to plan traffic-free optimal and smooth paths using the most spread open source navigation data structure, OpenStreetMaps. To that end, a procedure to automatically transform raw OSM data into the drivable space is combined with a MINLP optimization algorithm that finds the most suitable position of intermediate waypoints to connect Bézier primitive curves. The proposed planner is validated in a real complex roundabout, for which very smooth paths are generated, even considering obstacles.


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    Titel :

    Smooth path planning for urban autonomous driving using OpenStreetMaps


    Beteiligte:
    Artunedo, Antonio (Autor:in) / Godoy, Jorge (Autor:in) / Villagra, Jorge (Autor:in)


    Erscheinungsdatum :

    01.06.2017


    Format / Umfang :

    1106540 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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