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
2017-06-01
1106540 byte
Conference paper
Electronic Resource
English
Smooth Path Planning for Urban Autonomous Driving Using OpenStreetMaps
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