基于选择交叉烟花算法的无人车路径规划

doi:10.19678/j.issn.1000-3428.0062896

摘要/Abstract

摘要： 在三维地形环境下，基本烟花算法进行路径规划时易陷入局部最优解且存在收敛速度慢的问题，为此，提出选择交叉烟花算法。利用栅格法构建三维地形环境并设置威胁区域，使无人车选择合适的节点进行路径探索，结合燃耗代价、平滑代价和威胁代价构建适应度函数，以约束路径节点的生成位置，确保规划出的路径平滑且远离威胁区域。通过基本烟花算法的爆炸、变异、映射和选择操作进行路径搜索，同时加入针对路径节点的轮盘选择操作，使偏离原始路径较远的节点具有更高的爆炸概率，以约束路径的搜索方向，从而加快算法的搜索速度。在此基础上，引入选择交叉火花，通过对轮盘选择后节点间的路径片段进行交叉，以增强种群中烟花之间信息的交互性，提高搜索全局最优解的性能。仿真结果表明，相比基本烟花算法，该算法在简单和复杂地形环境下的适应度值平均提高6%，且运行时间平均缩短13.5%。在各类地形环境下，无人车通过该算法能有效规避威胁区域，并在较短时间内寻找到更加平滑且燃耗更低的路径。

关键词: 无人车, 路径规划, 三维环境, 烟花算法, 选择交叉火花

Abstract: In the three-dimensional terrain environment, the basic fireworks algorithm is easy to fall into the optimal solution and has the problem of slow convergence when path planning.A selection crossover fireworks algorithm is proposed.The grid method is used to build a three-dimensional terrain environment and set a threat area such that an unmanned vehicle can select appropriate nodes to explore the path.The fitness function is derived in combination with the fuel costs, smooth costs, and threat costs to restrict the generation position of the path nodes and ensure that the planned road path is smooth and far from the threat area.A path search is conducted via the explosion, mutation, mapping, and selection operations of the basic fireworks algorithm.In addition, the roulette selection operation for the path nodes is added such that the nodes farther from the original path have a higher explosion probability to restrict the search direction of the path, thereby speeding up the search speed of the algorithm.Based on this, a selection crossover spark is introduced to enhance the information interaction between fireworks in the population and improve the performance of searching the global optimal solution by crossing the path segments between nodes after wheel selection.The simulation results show that compared with the basic fireworks algorithm, the fitness of the proposed algorithm in the simple and complex terrain environments improves by 6% on average, and the running time shortens by 13.5% on average.In various terrain environments, the unmanned vehicle can successfully evade the threat area using the proposed algorithm and find a smoother path with lower fuel cost within a relatively short time.

Key words: unmanned vehicle, path planning, three-dimensional environment, fireworks algorithm, selection crossover spark

中图分类号:

TP391.9

高万博, 朱俊武, 章永龙, 章小卫. 基于选择交叉烟花算法的无人车路径规划[J]. 计算机工程, 2022, 48(11): 314-320.

GAO Wanbo, ZHU Junwu, ZHANG Yonglong, ZHANG Xiaowei. Unmanned Vehicle Path Planning Based on Selection Crossover Fireworks Algorithm[J]. Computer Engineering, 2022, 48(11): 314-320.

https://www.ecice06.com/CN/Y2022/V48/I11/314

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