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Path Planning with Multiple Obstacle-Avoidance Modes for Intelligent Vehicles
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Ziniu Hu1, Xinpeng Chen1, Zeyu Yang1, 2, Ziyun Yu1, Hongmao Qin1, Ming Gao1
Automotive Engineering | 2025, 47(3) : 402 - 411
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Automotive Engineering | 2025, 47(3): 402-411
• Feature Topic：Key Technologies on Intelligent and Connected Vehicles •
Path Planning with Multiple Obstacle-Avoidance Modes for Intelligent Vehicles
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Ziniu Hu1, Xinpeng Chen1, Zeyu Yang1, 2, Ziyun Yu1, Hongmao Qin1, Ming Gao1
Affiliations
  • 1 College of Mechanical and Vehicle Engineering，Hunan University，State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle，Changsha 410082
  • 2 Wuxi Intelligent Control Research Institute of Hunan University，Wuxi 214115
Published: 2025-03-25 doi: 10.19562/j.chinasae.qcgc.2025.03.002
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In unstructured scenes, there are often obstacles of various sizes, and the path planning process that only considers obstacle avoidance methods such as detours will lead to decrease in vehicle traffic efficiency. For these problems, in this paper an intelligent vehicle path planning method with multiple obstacleavoidance modes is proposed by integrating a layered collision detection strategy into the traditional Hybrid A* algorithm. Firstly, a doublelayer grid map is constructed based on the vehicle chassis height, and a layered collision detection strategy is designed using the body contour and fourwheel contour. Then, through a welldesigned heuristic function and cost function calculation method, the Hybrid A* algorithm can efficiently search for paths in multi obstacle scenes. Finally, the gradient descent method is used to smooth and optimize the path. Simulation and real vehicle experiment results demonstrate the effectiveness of the proposed algorithm in improving path search efficiency and significantly enhancing path smoothness. Moreover, the planned paths consider both crossing and bypassing strategies for obstacle avoidance, enabling vehicles to have better passability in multiobstacle scenarios.

path planning  /  hybrid A* algorithm  /  hierarchical collision detection strategy  /  gradient descent method
Ziniu Hu, Xinpeng Chen, Zeyu Yang, Ziyun Yu, Hongmao Qin, Ming Gao. Path Planning with Multiple Obstacle-Avoidance Modes for Intelligent Vehicles[J]. Automotive Engineering, 2025 , 47 (3) : 402 -411 . DOI: 10.19562/j.chinasae.qcgc.2025.03.002
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Article Info
doi: 10.19562/j.chinasae.qcgc.2025.03.002
  • Receive Date：2024-08-14
  • Online Date：2025-07-09
  • Published：2025-03-25
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History
  • Received：2024-08-14
  • Revised：2024-09-14
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Affiliations
    1 College of Mechanical and Vehicle Engineering，Hunan University，State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle，Changsha 410082
    2 Wuxi Intelligent Control Research Institute of Hunan University，Wuxi 214115
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https://castjournals.cast.org.cn/joweb/qcygc/EN/10.19562/j.chinasae.qcgc.2025.03.002
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