Improved Artificial Potential Field Modeling and Dynamic Obstacle Avoidance Path Planning for Continuous Curves

doi:10.3901/JME.260054

Abstract

Abstract: When employing the conventional artificial potential field(APF) algorithm for obstacle avoidance path planning on curves, the road APF does not reflect the impact of vehicle speed on safety risk, and the obstacle APF is easy to cause the fluctuation of the planned path. To address these deficiencies, an improved and comprehensive APF of traffic environment has been developed. Specifically, considering the risk of collisions due to vehicles deviating from the centerline of their lanes at high velocities during turns, a method has been proposed that dynamically adjusts the road boundary constraints based on vehicle velocity. This is implemented within the Frenet coordinate system to achieve an improved road APF. To accurately represent the collision risk characterized by the relative velocity between the vehicle and obstacles, the shortcomings of the traditional obstacle APF are analyzed. Based on a vector approach, a relative proximity coefficient is defined, leading to the establishment of an improved obstacle APF that considers both the relative proximity coefficient and the relative positional relationship, adapting to both static and dynamic obstacles. To validate the performance of these improved APFs, comparative analyses were conducted in a Carsim/Simulink joint simulation environment. The results indicate that the proposed improved road APF effectively reduces the extent to which vehicles deviate from the centerline of their lanes during high-speed turns, significantly lowering the risk of collisions with road boundaries. The improved obstacle APF, adjusting its distribution range dynamically based on the relative proximity coefficient, smoothly plans obstacle avoidance paths. The comprehensive APF of traffic environment, composed of the aforementioned two APFs, can more safely guide vehicles in navigating and avoiding obstacles on continuous curves.

Key words: intelligent vehicle, path planning, artificial potential field, obstacle avoidance

CLC Number:

U469

ZHANG Zhiyong, JIANG Zhihao, HU Lin, HUANG Caixia. Improved Artificial Potential Field Modeling and Dynamic Obstacle Avoidance Path Planning for Continuous Curves[J]. Journal of Mechanical Engineering, 2026, 62(2): 271-282.

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