Reinforcement Learning for Cooperative Overtaking

This paper solves the cooperative overtaking problem in autonomous driving using reinforcement learning techniques. Learning in such a situation is challenging due to vehicular mobility, which renders a continuously changing environment for each learning vehicle. Without no explicit coordination mechanisms, inefficient behaviors among vehicles might cause fatal uncoordinated outcomes. To solve this issue, we propose two basic coordination models to enable distributed learning of cooperative overtaking maneuvers in a group of vehicles. Extension mechanisms are then presented to make these models workable in more complex and realistic settings with any number of vehicles. Experiments verify that, by capturing the underlying consistency of identities or positions during vehicles’ movement, efficient coordinated behaviors can be achieved simply through vehicles’ local learning interactions.

Authors

• Chao Yu Sun Yat-sen University Pengcheng Laboratory
• Xin Wang
• Jianye Hao Tianjin University
• Zhanbo Feng

Keywords

• Reinforcement Learning
• Autonomous Driving
• Coordination
• Graph
• Cooperative Overtaking
• Multiagent Learning