Interactive Decision-making and Planning for Autonomous Driving Vehicles in Unsignalized Intersection

doi:10.3901/JME.2023.14.202

Abstract

Abstract: In order to solve the driving conservatism and the poor interaction of autonomous vehicles in unsignalized intersection, an interactive decision-making and planning algorithm is proposed. It can be divided into the following steps. Firstly, the motion of surrounding vehicles is tentatively predicted by the kinematic model-based method with road constraints. Based on this, the interactive action space of ego vehicle and the surrounding vehicle is built to cover the feasible driving range. Then, a novel threat assessment function is formulated that can evaluate the colliding risk of vehicles under any position, posture, and velocity. It is used for the solution of the state-action value. Furthermore, the Stackelberg Game is utilized to obtain the equilibrium action of ego vehicle and the interactive vehicle, which is the optimal action with considering the interaction in current traffic. Finally, the proposed algorithm is validated by the constructed intersection scenario in Prescan/Simulink. The results reveal that the proposed interactive algorithm can improve the efficiency by 7.3% and 12.4% compared to the decision-tree and the no-interaction method respectively while ensuring safety. Besides, it can also realize agile interaction in multi-vehicle complex interaction.

Key words: autonomous driving, decision-making and planning, interaction, threat assessment, unsignalized intersection

CLC Number:

U471

XU Can, ZHAO Wanzhong, LI Lin, ZHANG Ruijun, WANG Chunyan, CHEN Feng. Interactive Decision-making and Planning for Autonomous Driving Vehicles in Unsignalized Intersection[J]. Journal of Mechanical Engineering, 2023, 59(14): 202-212.

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