强化学习在自动驾驶技术中的应用与挑战  

Applications and Challenges of Reinforcement Learning in Autonomous Driving Technology

作　　者：何逸煦 林泓熠 刘洋[3] 杨澜[2] 曲小波[3] HE Yixu;LIN Hongyi;LIU Yang;YANG Lan;QU Xiaobo(School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,China;School of Information Engineering,Chang’an University,Xi’an 710064,China;School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China)

机构地区：[1]华南理工大学土木与交通学院,广东广州510640 [2]长安大学信息工程学院,陕西西安710064 [3]清华大学车辆与运载学院,北京100084

出　　处：《同济大学学报（自然科学版）》2024年第4期520-531,共12页Journal of Tongji University:Natural Science

基　　金：国家重点研发计划(2021YFB2501205);国家自然科学基金(52220105001,52221005,72322002,72361137001,72331001,52131204);长安大学研究生科研创新实践项目(300103723040)。

摘　　要：围绕强化学习在自动驾驶领域的应用进行了多方面的概括和总结。对强化学习原理及发展历程进行了介绍;系统介绍了自动驾驶技术体系以及强化学习在自动驾驶领域的应用所需的基础;按不同的应用方向分别介绍了强化学习在自动驾驶领域中的应用案例;深入分析了现阶段强化学习在自动驾驶领域存在的挑战,并提出若干展望。This paper provides a comprehensive overview and summary of the application of reinforcement learning in the field of autonomous driving.First,an introduction to the principles and development of reinforcement learning is presented.Following that,the autonomous driving technology system and the fundamentals required for the application of reinforcement learning in this field are systematically introduced.Subsequently,application cases of reinforcement learning in autonomous driving are described according to different directions of use.Finally,the current challenges of applying reinforcement learning in the field of autonomous driving are deeply analyzed,and several prospects are proposed.

关 键 词：强化学习 自动驾驶 人工智能 

分 类 号：U461[机械工程—车辆工程]