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. ; This work has been partially funded by the Spanish of Economy and Competitiveness with the National Projects TCAP-AUTO (RTC-2015-3942-4) and NAVEGASE (DPI2014-53525-C3-1-R) and by the European ECSEL JU Initiative in the EMC2 Project (621429) ; Peer Reviewed


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    Titel :

    Smooth path planning for urban autonomous driving using OpenStreetMaps



    Erscheinungsdatum :

    2017-06-11



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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