Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives
文献类型：期刊论文
| 作者 | Teng, Siyu2,3; Hu, Xuemin4; Deng, Peng4; Li, Bai5; Li, Yuchen2,3,6; Ai, Yunfeng7; Yang, Dongsheng8; Li, Lingxi1; Xuanyuan, Zhe9; Zhu, Fenghua10
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| 刊名 | IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
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| 出版日期 | 2023-06-01 |
| 卷号 | 8期号:6页码:3692-3711 |
| 关键词 | Motion planning pipeline planning end-to-end planning imitation learning reinforcement learning parallel learning |
| ISSN号 | 2379-8858 |
| DOI | 10.1109/TIV.2023.3274536 |
| 通讯作者 | Xuanyuan, Zhe(zhexuanyuan@uic.edu.cn) ; Zhu, Fenghua(fenghua.zhu@ia.ac.cn) ; Chen, Long(long.chen@ia.ac.cn) |
| 英文摘要 | Intelligent vehicles (IVs) have gained worldwide attention due to their increased convenience, safety advantages, and potential commercial value. Despite predictions of commercial deployment by 2025, implementation remains limited to small-scale validation, with precise tracking controllers and motion planners being essential prerequisites for IVs. This article reviews state-of-the-art motion planning methods for IVs, including pipeline planning and end-to-end planning methods. The study examines the selection, expansion, and optimization operations in a pipeline method, while it investigates training approaches and validation scenarios for driving tasks in end-to-end methods. Experimental platforms are reviewed to assist readers in choosing suitable training and validation strategies. A side-by-side comparison of the methods is provided to highlight their strengths and limitations, aiding system-level design choices. Current challenges and future perspectives are also discussed in this survey. |
| WOS关键词 | PARALLEL INTELLIGENCE ; OPTIMIZATION ; METAVERSES ; SCENARIOS ; VEHICLES ; VISION ; FRAMEWORK ; MODEL ; CAR |
| 资助项目 | NSFC[62273135] ; NSFC[2021CFB460] ; Natural Science Foundation of Hubei Province in China[62103139] ; 2022 Opening Foundation of State Key Laboratory of Management and Control for Complex Systems[E2S9021119] ; Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College[2022B1212010006] ; Guangdong Higher Education Upgrading Plan with UIC Research[R0400001-22] ; Guangdong Higher Education Upgrading Plan with UIC Research[R201902] |
| WOS研究方向 | Computer Science ; Engineering ; Transportation |
| 语种 | 英语 |
| WOS记录号 | WOS:001033547600017 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | NSFC ; Natural Science Foundation of Hubei Province in China ; 2022 Opening Foundation of State Key Laboratory of Management and Control for Complex Systems ; Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College ; Guangdong Higher Education Upgrading Plan with UIC Research |
| 源URL | [http://ir.ia.ac.cn/handle/173211/53924]  |
| 专题 | 多模态人工智能系统全国重点实验室 |
| 通讯作者 | Xuanyuan, Zhe; Zhu, Fenghua; Chen, Long |
| 作者单位 | 1.Indiana Univ Purdue Univ, Purdue Sch Engn & Technol, Indianapolis, IN USA 2.BNU HKBU United Int Coll, Zhuhai 519087, Peoples R China 3.Hong Kong Baptist Univ, Kowloon, Hong Kong 999077, Peoples R China 4.Hubei Univ, Sch Comp Sci & Informat Engn, Wuhan 430062, Peoples R China 5.State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Peoples R China 6.Hunan Univ, Coll Mech & Vehicle Engn, Changsha 410082, Peoples R China 7.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 8.Jinan Univ, Sch Publ Management Emergency Management, Guangzhou 510632, Peoples R China 9.BNU HKBU United Int Coll, Guangdong Prov Key Lab IRADS, Zhuhai, Peoples R China 10.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Teng, Siyu,Hu, Xuemin,Deng, Peng,et al. Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives[J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,2023,8(6):3692-3711. |
| APA | Teng, Siyu.,Hu, Xuemin.,Deng, Peng.,Li, Bai.,Li, Yuchen.,...&Chen, Long.(2023).Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives.IEEE TRANSACTIONS ON INTELLIGENT VEHICLES,8(6),3692-3711. |
| MLA | Teng, Siyu,et al."Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives".IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 8.6(2023):3692-3711. |
入库方式： OAI收割
来源：自动化研究所
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