利用改进人工势场法的智能车避障路径规划

Path planning for avoiding obstacles of autonomous vehicle using improved-artificial potential field

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 of local minimum on the autonomous vehicle obstacle avoidance path planning using artificial potential field, this paper adopted the improved-artificial potential method to finish autonomous vehicle obstacle avoidance path planning. Through the method of adjusting force field, improving potential field function and dynamically changing of repulsion coefficient, the situation of local minimum has been improved. The experimental results show that the improved-method has advantages in reducing the probability of falling into local minimum, and enhance the accuracy of the obstacle avoidance. The conclusion of the research has a great significance in promoting the accuracy and timeliness in autonomous vehicle obstacle avoidance path planning under complicated environment.