Lingyu Sun, Zhumu Fu, Fazhan Tao, Pengju Si, Shuzhong Song, and Chang Sun
Autonomous vehicle, artificial potential field, Bug algorithm, path planning, obstacle avoidance
With the increasing number of vehicles, driving environment is becoming increasingly complex and dynamic, which makes the driving of autonomous vehicle more difficult. In order to improve the safety of vehicle autonomous driving, in this paper, an improved artificial potential field (APF) path-planning algorithm for complex traffic environment with various obstacles is proposed. Considering the influence of vehicle physical characteristics on obstacle avoidance path, the repulsive potential field function of APF is improved. Then, aiming at the problem that traditional APF algorithm is easily fell into local extremum, a bug algorithm is introduced to ensure global performance of the proposed algorithm. Finally, feasibility and robustness of the proposed hybrid planning algorithm are validated by conducting several simulation investigations in a typical scenario.
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