Intelligent Vehicle Path Planning Based on Improved Artificial Potential Field Algorithm

Abstract

Goal unreachable problem and local minimum point problem appear when the traditional artificial potential field (APF) method is used for intelligent vehicle path planning. Aiming at the problem of goal unreachable with obstacle nearby, a modified repulsion potential field function is proposed in this paper to realize the regulation of potential field. The modified repulsion potential field introduces the relative distance between the intelligent vehicle and the target point, and at the same time increases the regulation factor to ensure that the minimum potential point of the whole situation field is always at the target point. In order to solve the local minimum problem caused by the traditional artificial potential field method in path planning, this paper introduces the fuzzy control (FC) algorithm based on the improved artificial potential field algorithm, proposes the APF-FC fusion algorithm, and uses the fuzzy control of fuzzy control algorithm to solve the local minimum problem of APF. Finally, the APF-FC path planning algorithm is simulated. The verification results show that the algorithm combines the characteristics of artificial potential field and fuzzy algorithm well, and effectively solves the related defects of traditional artificial potential field algorithm. The effectiveness and applicability of the path planning of the algorithm are significantly improved.