中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Design and implementation of an adaptive cruise control system based on supervised actor-critic learning

文献类型:会议论文

作者Wang,Bin; Zhao,Dongbin; Li,Chengdong; Dai,Yujie
出版日期2015
会议日期April 24–26, 2015
会议地点Hunan, China
关键词Adaptive Cruise Control System Level Control Acceleration Control
英文摘要A novel adaptive cruise control (ACC) system is proposed in this paper. A hierarchical control framework is adopted for the adaptive cruise control problem. For the upper level, a supervised actor-critic (SAC) reinforcement learning approach is presented to obtain the desired acceleration controller. In the lower level, throttle and brake controllers calculate the required throttle and/or brake signals based on the desired longitudinal acceleration. Feed-forward neural networks are used to implement the actor and critic components of the SAC learning algorithm. An online learning mechanism is introduced to implement the SAC training process. dSPACE simulator is used to verify the effectiveness of the ACC system. Typical emergency braking scenario is simulated to test the adaptability of the ACC system. Road condition change (e.g. wintry or wet conditions) simulation is first investigated to evaluate the robustness of the ACC system. Performance of the proposed ACC system is proved to be very practical.
源URL[http://ir.ia.ac.cn/handle/173211/19887]  
专题复杂系统管理与控制国家重点实验室_深度强化学习
推荐引用方式
GB/T 7714
Wang,Bin,Zhao,Dongbin,Li,Chengdong,et al. Design and implementation of an adaptive cruise control system based on supervised actor-critic learning[C]. 见:. Hunan, China. April 24–26, 2015.

入库方式: OAI收割

来源:自动化研究所

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