Paper
10 October 2023 A hierarchical path planning algorithm based on graphical search and optimization methods
Author Affiliations +
Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279942 (2023) https://doi.org/10.1117/12.3006128
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia
Abstract
This paper proposes a hierarchical path-planning algorithm based on a combination of graphical search algorithms and optimization methods. In the global path planning layer, by using the Hybrid A* algorithm, we can quickly obtain an optimal path that can avoid all static obstacles on the map. In the local path planning layer, the global path is optimized by numerical nonlinear numerical optimization to generate a feasible path that satisfies the safety constraints. By processing global path planning and local path planning separately, the computational complexity of path planning can be effectively reduced, and the efficiency and accuracy of the path planning can be improved. Secondly, the hybrid planning algorithm can generate high-quality paths with both safety and flexibility. We simulate and verify the algorithm, and the results show that the method has practical applications in autonomous driving.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Liang Wu, Chengzhi Yi, Chao Cheng, and Dongxuan Xie "A hierarchical path planning algorithm based on graphical search and optimization methods", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279942 (10 October 2023); https://doi.org/10.1117/12.3006128
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KEYWORDS
Autonomous vehicles

Mathematical optimization

Autonomous driving

Safety

Roads

Unmanned vehicles

Computer simulations

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