Counterfactual Evolutionary Reasoning for Virtual Driver Reinforcement Learning in Safe Driving
文献类型：期刊论文
| 作者 | Ye, Peijun2 ; Qi, Hao1; Zhu, Fenghua2; Lv, Yisheng2
|
| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 8期号:12页码:4696-4705 |
| ISSN号 | 2379-8858 |
| 关键词 | Safe driving reinforcement learning counter factual reasoning evolutionary search |
| DOI | 10.1109/TIV.2023.3322694 |
| 通讯作者 | Ye, Peijun(peijun_ye@hotmail.com) |
| 英文摘要 | 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. |
| WOS关键词 | VEHICLES |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Computer Science ; Engineering ; Transportation |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:001140418700007 |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55470]  |
| 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.Shandong Jiaotong Univ, Sch Rail Transportat, Jinan 250357, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence, Beijing 100190, Peoples R China |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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