Autonomous Exploration for Automated Valet Parking Based on Road Structure

Abstract

Automated valet parking technology allows the vehicle to automatically drive into the parking lot and park itself without a human in the vehicle, relieving humans from parking completely. However, the existing automated valet parking system relies on infrastructural intelligence or pre-acquisition of parking lot maps. Given the disadvantages of these researches, this paper proposes a general method for automatic valet parking system based on autonomous exploration. This method depends on no prior knowledge of the parking lot. Our method extracts road structure from perception result using the Voronoi diagram. A multi-factor exploration strategy we proposed is used to generate exploration candidates for autonomous exploration from the road structure. Also, a motion planning method based on the lateral priority of the road guides the vehicle to the candidates while obeys the rules as far as possible. The autonomous exploration will continue until it finds free parking slots or all the spaces in the parking lot are explored. Related experiments have verified the effectiveness of the method presented in this paper.