基于遗传模糊算法的智能车辆避障路径规划研究
Path planning of intelligent vehicle based on genetic fuzzy algorithm

利用模糊逻辑和遗传算法构建一种智能车辆避障路径规划方法. 首先建立智能车辆的动力学模型，然后设计模糊控制器，以智能车辆与目标点及障碍物中心点的角度差、智能车辆与障碍物的距离为输入量，智能车辆的速度、转角为输出量分别建立避障行为模糊规则表和趋向目标模糊规则表，最后利用遗传算法对避障行为模糊规则表进行优化. 仿真结果表明，该方法是正确和有效的.
A method of path planning based on fuzzy logic and genetic algorithm is proposed. Firstly，the dynamic model and kinetic equations of intelligent vehicle are constructed. Afterward，fuzzy logic control is designed. The angle between the obstacle and the goal，and the distance between the obstacle and intelligent vehicle are taken as inputs，the speed and corner of intelligent vehicle are taken as output，obstacle-avoiding and goal-trending fuzzy inference rules are established. Finally，a genetic algorithm is used for optimization obstacle-avoiding fuzzy inference rules. The simulation result shows that the proposed method of path planning based on fuzzy logic and genetic algorithm is correct and efficient