基于改进遗传算法的路径规划与跟踪控制统一建模

Ziqing Wang, Zhumu Fu
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引用次数: 0

摘要

车辆路径规划和跟踪控制是实现自动驾驶的关键。本文提出了一种基于人工势场算法和遗传算法的组合算法。基于车辆行驶环境信息,建立不同环境下的势场函数。并利用所建立的人工势场对遗传算法中的初始种群进行优化。规划一条可靠的行驶路线。采用模型预测控制算法。规划路径的跟踪控制。实现了统一建模。实验结果表明,改进的路径规划算法和跟踪控制方法能够很好地规划和跟踪路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unified Modeling of Path Planning and Tracking Control Based on Improved Genetic Algorithm
Vehicle path planning and tracking control are the key to achieving autonomous driving. In this paper, a combined algorithm based on artificial potential field algorithm and genetic algorithm is proposed. Based on information about the vehicle's driving environment, establishing potential field functions in different environments. And the initialized populations in the genetic algorithm are optimized using the established artificial potential fields. Planning a reliable driving path. Using model predictive control algorithms. Tracking control of the planned path. Unified modeling was achieved. Experimental results show that the improved path planning algorithm and tracking control method are able to plan and track the path well.
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