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Local Path Planning for Off-Road Autonomous Driving With Avoidance of Static Obstacles

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3 Author(s)
Keonyup Chu ; Automotive Control and Electronics Laboratory, Department of Automotive Engineering, Hanyang University, Seoul, Korea ; Minchae Lee ; Myoungho Sunwoo

In this paper, a real-time path-planning algorithm that provides an optimal path for off-road autonomous driving with static obstacles avoidance is presented. The proposed planning algorithm computes a path based on a set of predefined waypoints. The predefined waypoints provide the base frame of a curvilinear coordinate system to generate path candidates for autonomous vehicle path planning. Each candidate is converted to a Cartesian coordinate system and evaluated using obstacle data. To select the optimal path, the priority of each path is determined by considering the path safety cost, path smoothness, and path consistency. The proposed path-planning algorithms were applied to the autonomous vehicle A1, which won the 2010 Autonomous Vehicle Competition organized by the Hyundai-Kia Automotive Group in Korea.

Published in:

IEEE Transactions on Intelligent Transportation Systems  (Volume:13 ,  Issue: 4 )