Knowledge Commons of Institute of Automation,CAS
Counterfactual Evolutionary Reasoning for Virtual Driver Reinforcement Learning in Safe Driving | |
Ye, Peijun1; Qi, Hao2; Zhu, Fenghua1; Lv, Yisheng1 | |
发表期刊 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES |
ISSN | 2379-8858 |
2023-12-01 | |
卷号 | 8期号:12页码:4696-4705 |
通讯作者 | Ye, Peijun(peijun_ye@hotmail.com) |
摘要 | Safety is the primary concern in the motion planning and decision-making of the virtual driver that provides prescriptions to the real human driver and even performs self-driving in the absence of human take-over. For such an issue, traditional reinforcement learning methods, limited by their learning mechanisms, suffer from a slow convergence of model training as well as a less consideration for early warning of possible accidents. To address the above deficiency, this paper proposes a new method based on counterfactual evolutionary reasoning that can be used to build the virtual driver. The method treats safe driving as a sequential decision-making problem with sparse rewards, and employs counterfactual evolutionary reasoning to guide the searching direction as well as to accelerate the model training. An intervention mechanism from outlier distributions is further introduced to enhance the model's ability of exploration. Experiments in the virtual test environment indicate that the proposed method, compared with other typical reinforcement learning techniques, both achieves a higher safe arrival rate and a faster convergence speed. |
关键词 | Safe driving reinforcement learning counter factual reasoning evolutionary search |
DOI | 10.1109/TIV.2023.3322694 |
关键词[WOS] | VEHICLES |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China |
项目资助者 | National Natural Science Foundation of China |
WOS研究方向 | Computer Science ; Engineering ; Transportation |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS记录号 | WOS:001140418700007 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/55471 |
专题 | 多模态人工智能系统全国重点实验室 |
通讯作者 | Ye, Peijun |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing 100190, Peoples R China 2.Shandong Jiaotong Univ, Sch Rail Transportat, Jinan 250357, 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 | Ye, Peijun,Qi, Hao,Zhu, Fenghua,et al. Counterfactual Evolutionary Reasoning for Virtual Driver Reinforcement Learning in Safe Driving[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(12):4696-4705. |
APA | Ye, Peijun,Qi, Hao,Zhu, Fenghua,&Lv, Yisheng.(2023).Counterfactual Evolutionary Reasoning for Virtual Driver Reinforcement Learning in Safe Driving.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(12),4696-4705. |
MLA | Ye, Peijun,et al."Counterfactual Evolutionary Reasoning for Virtual Driver Reinforcement Learning in Safe Driving".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.12(2023):4696-4705. |
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