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.
Smooth path planning for urban autonomous driving using OpenStreetMaps
01.06.2017
1106540 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Smooth Path Planning for Urban Autonomous Driving Using OpenStreetMaps
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