| Title | Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives |
| Creator | |
| Date Issued | 2023-06-01 |
| Source Publication | IEEE Transactions on Intelligent Vehicles
 |
| Volume | 8Issue:6Pages:3692-3711 |
| Abstract | 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. |
| Keyword | end-to-end planning imitation learning Motion planning parallel learning pipeline planning reinforcement learning |
| DOI | 10.1109/TIV.2023.3274536 |
| URL | View source |
| Language | 英语English |
| Scopus ID | 2-s2.0-85159838341 |
| Citation statistics | |
| Document Type | Journal article |
| Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/11581 |
| Collection | Beijing Normal-Hong Kong Baptist University |
| Corresponding Author | Xuanyuan，Zhe |
| Affiliation | 1.BNU-HKBU United International College,Guangdong Provincial Key Lab of IRADS,Zhuhai,519087,China 2.Hong Kong Baptist University,Kowloon,999077,Hong Kong 3.Hubei University,School of Computer Science and Information Engineering,Wuhan,430062,China 4.State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body,Changsha,410082,China 5.Hunan University,College of Mechanical and Vehicle Engineering,Changsha,410082,China 6.University of Chinese Academy of Sciences,Beijing,100049,China 7.Jinan University,School of Public Management/Emergency Management,Guangzhou,510632,China 8.Indiana University-Purdue University Indianapolis,Purdue School of Engineering and Technology,Indianapolis,46202,United States 9.Chinese Academy of Sciences,Institute of Automation,Beijing,100190,China 10.Waytous Ltd.,China |
| First Author Affilication | Beijing Normal-Hong Kong Baptist University |
| Corresponding Author Affilication | Beijing Normal-Hong Kong Baptist University |
| Recommended Citation GB/T 7714 | Teng，Siyu,Hu，Xuemin,Deng，Penget 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. |
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