文章基本信息

标题：Heuristic Reinforcement Learning Based Overtaking Decision for an Autonomous Vehicle
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作者：Guodong Du ; Yuan Zou ; Xudong Zhang 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：10
页码：59-66
DOI：10.1016/j.ifacol.2021.10.141
语种：English
出版社：Elsevier
摘要：AbstractThis paper proposes an intelligent overtaking decision based on the heuristic reinforcement learning method for an autonomous vehicle. The proposed overtaking control focuses on the safety and efficiency of the autonomous vehicle driving. Firstly, the overtaking problem is modeled and the adaptive safe driving area is constructed. Then, a heuristic reinforcement learning method called Heu-Dyna is developed to derive the optimal overtaking decision, which introduces the heuristic planning function. Besides, the generalized correlation coefficient is designed to evaluate the training perfection of the control strategy. The simulation results show that the performance of the proposed method on the rapidity and optimality is superior to the Q-learning method and the Dyna method. Furthermore, the adaptability of the proposed method is validated by applying different driving conditions.
关键词：KeywordsAutonomous vehicleOvertaking decisionReinforcement learningHeuristic planningGeneralized correlation coefficient