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原文传递 Data-driving Reinforcement Learning on the Path Planning for Autonomous Vehicles

题名：	Data-driving Reinforcement Learning on the Path Planning for Autonomous Vehicles
正文语种：	中文
作者：	Fang Xiao Xie Ping Gao Hongbo He Qun Li Naiyi
作者单位：	hery Scientific Research Institute Wuhu;Shanghai Jiao Tong University Yanshan University hery Scientific Research Institute Wuhu;Nanjing University of Science and Technology hery Scientific Research Institute Wuhu 4
关键词：	autonomous vehicle path planning reinforcement learning adaptive dynamic programming
摘要：	The path planning for autonomous vehicles is a hot topic in academic world.The goal of this problem is to design a vehi-cle with learning ability to approach the target without any collision.In this paper,we focus on data-driving reinforcement learning(RL)design for the path planning for autonomous vehicles problems.We proposed the method of sensor detection,and a self-learning strategy for a vehicle seeking the target with obstacle avoidance.Specifically,we designed a continuous reinforcement signal to improve the system ' s preferential decision between the target seeking and the obstacle avoidance.To verify the learning ability of our strategy,we developed an in-door environment with different experiments.The simulation results show that the RL presents an effective learning ability for the path planning for autonomous vehicles problems.
会议日期：	20161026
会议举办地点：	上海
会议名称：	2016中国汽车工程学会年会
出版日期：	2016-10-26
母体文献：	2016中国汽车工程学会年会论文集