强化学习在自动驾驶技术中的应用与挑战OA北大核心CSTPCD
Applications and Challenges of Reinforcement Learning in Autonomous Driving Technology
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.
何逸煦;林泓熠;刘洋;杨澜;曲小波
华南理工大学 土木与交通学院,广东 广州 510640||长安大学 信息工程学院,陕西西安 710064清华大学 车辆与运载学院,北京 100084长安大学 信息工程学院,陕西西安 710064
交通运输
强化学习自动驾驶人工智能
reinforcement learningautonomous drivingartificial intelligence
《同济大学学报(自然科学版)》 2024 (004)
520-531 / 12
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)
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