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Model-free Optimal Control based Intelligent Cruise Control with Hardware-in-the-loop Demonstration
Zhao, Dongbin1,2,3; Xia, Zhongpu4; Zhang, Qichao1,2
Source PublicationIEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
2017-05-01
Volume12Issue:2Pages:56-69
SubtypeArticle
AbstractIt is difficult to implement optimal control for a system whose model is unknown and operation environment is uncertain, such as the intelligent cruise control of vehicles. This article will address the problem from the perspective of reinforcement learning by learning the optimal policy from the state transition data. The model-free optimal control algorithm is employed to approximate the optimal control policy for the intelligent cruise control system, which considers the comfort performance and the safety performance comprehensively by setting up a total performance index. The algorithm is implemented by two multi-layer neural networks which are the critic network and the actor network. The critic and actor networks are employed to approximate the state-action value function and the control action, respectively. In addition, a data collecting strategy is proposed to obtain the state transition data distributed uniformly in the state action space from the running trajectory of the host car. The critic network and the action network are trained alternatively by the collected data until converging. The convergent action network is used to obtain the optimal control policy. At last, the policy is tested on a hardware-in-the-loop simulator built upon dSPACE by comparing with a linear quadratic regulator (LQR) controller and a proportion integration differentiation (PID) controller. Results show its excellent performance on both aspects of the safety and the comfort.
KeywordIntelligent Cruise Control
WOS HeadingsScience & Technology ; Technology
DOI10.1109/MCI.2017.2670463
WOS KeywordLONGITUDINAL CONTROL ; POLICY ITERATION ; CONTROL DESIGN ; AVOIDANCE ; VEHICLES ; SYSTEM
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China (NSFC)(61573353 ; National Key Research and Development Plan(2016YFB0101000) ; 61533017)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000399714900005
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14337
Collection复杂系统管理与控制国家重点实验室_深度强化学习
Corresponding AuthorZhang, Qichao
Affiliation1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Jiangsu Huimin Traff Facil Co Ltd, Huaian, Jiangsu, Peoples R China
4.Baidu Com Times Technol Co Ltd, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Zhao, Dongbin,Xia, Zhongpu,Zhang, Qichao. Model-free Optimal Control based Intelligent Cruise Control with Hardware-in-the-loop Demonstration[J]. IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE,2017,12(2):56-69.
APA Zhao, Dongbin,Xia, Zhongpu,&Zhang, Qichao.(2017).Model-free Optimal Control based Intelligent Cruise Control with Hardware-in-the-loop Demonstration.IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE,12(2),56-69.
MLA Zhao, Dongbin,et al."Model-free Optimal Control based Intelligent Cruise Control with Hardware-in-the-loop Demonstration".IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 12.2(2017):56-69.
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