A Method for Autonomous Driving Trajectory Planning in Parking Environments
Local trajectory planning is one of the key technologies of the autonomous valet parking system. In this scenario, there exist problems such as long planning time, discontinuous curvature, and insufficient safety in local trajectory planning methods for intelligent vehicles. Aimed at these problems,...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Shanghai Jiao Tong University
2023-03-01
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| Series: | Shanghai Jiaotong Daxue xuebao |
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| Online Access: | https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-3-345.shtml |
| _version_ | 1827976717303545856 |
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| author | LIN Chun, HE Yuesheng, FANG Xingqi, WANG Chunxiang |
| author_facet | LIN Chun, HE Yuesheng, FANG Xingqi, WANG Chunxiang |
| author_sort | LIN Chun, HE Yuesheng, FANG Xingqi, WANG Chunxiang |
| collection | DOAJ |
| description | Local trajectory planning is one of the key technologies of the autonomous valet parking system. In this scenario, there exist problems such as long planning time, discontinuous curvature, and insufficient safety in local trajectory planning methods for intelligent vehicles. Aimed at these problems, this paper proposes a trajectory planning method for intelligent vehicles in parking scenarios. This method improves the real-time performance and security of the initial path search by improving the analytic expansions of the hybrid A* algorithm and introducing the risk function. Further, according to the initial path, the quadratic programming method is used to realize path smoothing and speed planning. Finally, the trajectory generation is completed. Simulation experiments show that the method can improve the real-time, smoothness, and safety of intelligent vehicle trajectory planning. In addition, in actual parking environment, the feasibility of the method is verified in real-world vehicle experiments. |
| first_indexed | 2024-04-09T20:41:03Z |
| format | Article |
| id | doaj.art-48974eddeff248469489137de207159f |
| institution | Directory Open Access Journal |
| issn | 1006-2467 |
| language | zho |
| last_indexed | 2024-04-09T20:41:03Z |
| publishDate | 2023-03-01 |
| publisher | Editorial Office of Journal of Shanghai Jiao Tong University |
| record_format | Article |
| series | Shanghai Jiaotong Daxue xuebao |
| spelling | doaj.art-48974eddeff248469489137de207159f2023-03-30T03:21:10ZzhoEditorial Office of Journal of Shanghai Jiao Tong UniversityShanghai Jiaotong Daxue xuebao1006-24672023-03-0157334535310.16183/j.cnki.jsjtu.2021.443A Method for Autonomous Driving Trajectory Planning in Parking EnvironmentsLIN Chun, HE Yuesheng, FANG Xingqi, WANG Chunxiang0Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, ChinaLocal trajectory planning is one of the key technologies of the autonomous valet parking system. In this scenario, there exist problems such as long planning time, discontinuous curvature, and insufficient safety in local trajectory planning methods for intelligent vehicles. Aimed at these problems, this paper proposes a trajectory planning method for intelligent vehicles in parking scenarios. This method improves the real-time performance and security of the initial path search by improving the analytic expansions of the hybrid A* algorithm and introducing the risk function. Further, according to the initial path, the quadratic programming method is used to realize path smoothing and speed planning. Finally, the trajectory generation is completed. Simulation experiments show that the method can improve the real-time, smoothness, and safety of intelligent vehicle trajectory planning. In addition, in actual parking environment, the feasibility of the method is verified in real-world vehicle experiments.https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-3-345.shtmlautonomous vehiclesparking environmentstrajectory planninghybrid <i>a</i><sup>*</sup> algorithmquadratic programming |
| spellingShingle | LIN Chun, HE Yuesheng, FANG Xingqi, WANG Chunxiang A Method for Autonomous Driving Trajectory Planning in Parking Environments Shanghai Jiaotong Daxue xuebao autonomous vehicles parking environments trajectory planning hybrid <i>a</i><sup>*</sup> algorithm quadratic programming |
| title | A Method for Autonomous Driving Trajectory Planning in Parking Environments |
| title_full | A Method for Autonomous Driving Trajectory Planning in Parking Environments |
| title_fullStr | A Method for Autonomous Driving Trajectory Planning in Parking Environments |
| title_full_unstemmed | A Method for Autonomous Driving Trajectory Planning in Parking Environments |
| title_short | A Method for Autonomous Driving Trajectory Planning in Parking Environments |
| title_sort | method for autonomous driving trajectory planning in parking environments |
| topic | autonomous vehicles parking environments trajectory planning hybrid <i>a</i><sup>*</sup> algorithm quadratic programming |
| url | https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-3-345.shtml |
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