Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC
Abstract The rapid acceleration of urbanization and the surge in car ownership necessitate efficient automatic parking solutions in constricted spaces to address the escalating urban parking issue. To optimize space utilization, enhance traffic efficiency, and mitigate accident risks, a method is pr...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-85541-x |
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| _version_ | 1841544565844082688 |
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| author | Pei Zhang SiLong Zhou Jie Hu WenLong Zhao Jiachen Zheng Zhiling Zhang Chongzhi Gao |
| author_facet | Pei Zhang SiLong Zhou Jie Hu WenLong Zhao Jiachen Zheng Zhiling Zhang Chongzhi Gao |
| author_sort | Pei Zhang |
| collection | DOAJ |
| description | Abstract The rapid acceleration of urbanization and the surge in car ownership necessitate efficient automatic parking solutions in constricted spaces to address the escalating urban parking issue. To optimize space utilization, enhance traffic efficiency, and mitigate accident risks, a method is proposed for smooth, comfortable, and adaptable automatic parking trajectory planning. This study initially employs a hybrid A* algorithm to generate a preliminary path, then fits the velocity and acceleration based on a cubic polynomial. The kinematic constraints of the vehicle and obstacle avoidance constraints are then meticulously defined, and a coupled nonlinear model predictive control (NMPC) method is employed to optimize the trajectory. Compared to the hybrid A* algorithm, the optimized trajectory demonstrates superior space utilization and improved smoothness. The experimental results indicate that the proposed method performs effectively in automated parking tasks in confined spaces, suggesting promising applications and broad prospects for future. |
| format | Article |
| id | doaj-art-19be03bd0ee243dfabac8ea46d002c7d |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-19be03bd0ee243dfabac8ea46d002c7d2025-01-12T12:24:08ZengNature PortfolioScientific Reports2045-23222025-01-0115111510.1038/s41598-025-85541-xAutomatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPCPei Zhang0SiLong Zhou1Jie Hu2WenLong Zhao3Jiachen Zheng4Zhiling Zhang5Chongzhi Gao6Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology)Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology)Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology)Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology)Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology)Hubei Key Laboratory of Modern Auto Parts Technology (Wuhan University of Technology)Commercial Product R&D Institute, Dongfeng Automobile Co., Ltd.Abstract The rapid acceleration of urbanization and the surge in car ownership necessitate efficient automatic parking solutions in constricted spaces to address the escalating urban parking issue. To optimize space utilization, enhance traffic efficiency, and mitigate accident risks, a method is proposed for smooth, comfortable, and adaptable automatic parking trajectory planning. This study initially employs a hybrid A* algorithm to generate a preliminary path, then fits the velocity and acceleration based on a cubic polynomial. The kinematic constraints of the vehicle and obstacle avoidance constraints are then meticulously defined, and a coupled nonlinear model predictive control (NMPC) method is employed to optimize the trajectory. Compared to the hybrid A* algorithm, the optimized trajectory demonstrates superior space utilization and improved smoothness. The experimental results indicate that the proposed method performs effectively in automated parking tasks in confined spaces, suggesting promising applications and broad prospects for future.https://doi.org/10.1038/s41598-025-85541-xAutomatic parkingHybrid A* algorithmCubic polynomialNMPCOptimal controlCollision constraint |
| spellingShingle | Pei Zhang SiLong Zhou Jie Hu WenLong Zhao Jiachen Zheng Zhiling Zhang Chongzhi Gao Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC Scientific Reports Automatic parking Hybrid A* algorithm Cubic polynomial NMPC Optimal control Collision constraint |
| title | Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC |
| title_full | Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC |
| title_fullStr | Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC |
| title_full_unstemmed | Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC |
| title_short | Automatic parking trajectory planning in narrow spaces based on Hybrid A* and NMPC |
| title_sort | automatic parking trajectory planning in narrow spaces based on hybrid a and nmpc |
| topic | Automatic parking Hybrid A* algorithm Cubic polynomial NMPC Optimal control Collision constraint |
| url | https://doi.org/10.1038/s41598-025-85541-x |
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