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为解决智能车避障路径规划中采用人工势场法易陷入局部极小值的问题,采用改进的人工势场法进行智能车避障规划方法,通过调整势力场范围、改进斥力势函数和动态调整斥力场系数对人工势场法进行改进,解决陷入局部极小值的情况.研究结果表明:改进后的方法大大减小了智能车陷入局部极小值的概率,增加了避障的准确性.研究结论对提高复杂环境中智能车避障路径选择的准确性和实时性有重要意义.
In order to solve the problem that artificial potential field method is easy to fall into local minima in obstacle avoidance path planning of intelligent vehicles, an improved artificial potential field method is adopted to solve the obstacle avoidance planning of intelligent vehicles. By adjusting the range of force field and improving the repulsion potential function and dynamics Adjust the repulsion field coefficient to improve the artificial potential field method and solve the situation of falling into a local minimum.The results show that the improved method can greatly reduce the probability of getting into the local minimum and increase the accuracy of obstacle avoidance The conclusion of the study is of great significance to improve the accuracy and the real - time performance of obstacle avoidance route selection in the complex environment.