Knowledge Commons of Institute of Automation,CAS
Adaptive cruise control via adaptive dynamic programming with experience replay | |
Wang, Bin1,2; Zhao, Dongbin2; Cheng, Jin1 | |
发表期刊 | SOFT COMPUTING |
ISSN | 1432-7643 |
2019-06-01 | |
卷号 | 23期号:12页码:4131-4144 |
通讯作者 | Wang, Bin(cse_wangb@ujn.edu.cn) |
摘要 | The adaptive cruise control (ACC) problem can be transformed to an optimal tracking control problem for complex nonlinear systems. In this paper, a novel highly efficient model-free adaptive dynamic programming (ADP) approach with experience replay technology is proposed to design the ACC controller. Experience replay increases the data efficiency by recording the available driving data and repeatedly presenting them to the learning procedure of the acceleration controller in the ACC system. The learning framework that combines ADP with experience replay is described in detail. The distinguishing feature of the algorithm is that when estimating parameters of the critic network and the actor network with gradient rules, the gradients of historical data and current data are used to update parameters concurrently. It is proved with Lyapunov theory that the weight estimation errors of the actor network and the critic network are uniformly ultimately bounded under the novel weight update rules. The learning performance of the ACC controller implemented by this ADP algorithm is clearly demonstrated that experience replay can increase data efficiency significantly, and the approximate optimality and adaptability of the learned control policy are tested with typical driving scenarios. |
关键词 | Adaptive cruise control Adaptive dynamic programming Experience replay Reinforcement learning Neural networks |
DOI | 10.1007/s00500-018-3063-7 |
关键词[WOS] | SYSTEMS ; DESIGN |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61603150] ; National Natural Science Foundation of China[61273136] ; National Natural Science Foundation of China[61573353] ; National Natural Science Foundation of China[61533017] ; National Key Research and Development Plan[2016YFB0101000] ; Doctoral Foundation of University of Jinan[XBS1605] ; National Natural Science Foundation of China[61603150] ; National Natural Science Foundation of China[61273136] ; National Natural Science Foundation of China[61573353] ; National Natural Science Foundation of China[61533017] ; National Key Research and Development Plan[2016YFB0101000] ; Doctoral Foundation of University of Jinan[XBS1605] ; National Natural Science Foundation of China[61603150] ; National Natural Science Foundation of China[61273136] ; National Natural Science Foundation of China[61573353] ; National Natural Science Foundation of China[61533017] ; National Key Research and Development Plan[2016YFB0101000] ; Doctoral Foundation of University of Jinan[XBS1605] |
项目资助者 | National Natural Science Foundation of China ; National Key Research and Development Plan ; Doctoral Foundation of University of Jinan |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications |
WOS记录号 | WOS:000466948100018 |
出版者 | SPRINGER |
七大方向——子方向分类 | 强化与进化学习 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/24397 |
专题 | 多模态人工智能系统全国重点实验室_深度强化学习 |
通讯作者 | Wang, Bin |
作者单位 | 1.Univ Jinan, Sch Elect Engn, Jinan 250022, Shandong, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wang, Bin,Zhao, Dongbin,Cheng, Jin. Adaptive cruise control via adaptive dynamic programming with experience replay[J]. SOFT COMPUTING,2019,23(12):4131-4144. |
APA | Wang, Bin,Zhao, Dongbin,&Cheng, Jin.(2019).Adaptive cruise control via adaptive dynamic programming with experience replay.SOFT COMPUTING,23(12),4131-4144. |
MLA | Wang, Bin,et al."Adaptive cruise control via adaptive dynamic programming with experience replay".SOFT COMPUTING 23.12(2019):4131-4144. |
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