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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    Title :

    Smooth path planning for urban autonomous driving using OpenStreetMaps


    Contributors:


    Publication date :

    2017-06-01


    Size :

    1106540 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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