基于混合算法的智能车辆路径规划

Fan Bailin, Ren Haixiao, Deng Zhangshen, Chen Jianhua
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引用次数: 1

摘要

针对智能汽车在复杂环境下的路径规划问题,提出了一种混合路径规划算法。在混合算法中,将A *算法与人工势场法相结合。混合算法充分吸收了两种算法的优点,弥补了各自算法的不足。分别改进了传统A *算法和人工势场法存在的问题。然后,将两种改进算法进行合并。采用A *算法求出最短路径。改进的人工势场法可以有效地避开道路上的各种障碍物。上述混合算法弥补了A *算法不能应用于动态环境、人工势场法不能规划最短路径的不足。通过MATLAB软件验证了改进算法和混合算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Vehicle Path Planning Based on Hybrid Algorithm
Aiming at the path planning problem of smart cars in complex environments, a hybrid algorithm was proposed for path planning. In the hybrid algorithm, the A * algorithm was combined with the artificial potential field method. The hybrid algorithm fully absorbed the advantages of the two algorithms and made up for the shortcomings of their respective algorithms. The existing problems of traditional A * algorithm and artificial potential field method were improved respectively. Then, the two improved algorithms were merged. And the shortest path was obtained by using A * algorithm. The improved artificial potential field method could effectively avoid various obstacles on the road. The hybrid algorithm appearing above made up for the shortcomings that the A * algorithm couldn't be applied to dynamic environments, and the artificial potential field method couldn't plan the shortest path. The effectiveness of the improved algorithm and hybrid algorithm was verified by MATLAB software.
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