Artificial potential field optimization algorithm for autonomous vessel emergency collision avoidance scenarios based on TCPA and DCPA
WANG Zongkai
SUN Qiang
LIU Yang
IM Namkyun
Abstract：To address the local optimum problem of the traditional artificial potential field(T-APF)algorithm and the limitations of dynamic obstacle avoidance in emergency collision avoidance scenarios for autonomous vessels,an enhanced artificial potential field(E-APF)algorithm based on time to closest point of approach(TCPA)and distance to closest point of approach(DCPA)is proposed.This algorithm reconstructs the repulsive potential field function,introduces a dynamic weight adjustment mechanism,and combines relative motion dynamics to design an adaptive repulsive direction strategy.Simulation results indicate that in static obstacle scenarios,the E-APF algorithm can identify collision risks earlier and plan better paths compared to the T-APF algorithm;in dynamic obstacle scenarios,it effectively increases safety distances and reduces steering angles,significantly improving the accuracy of obstacle risk assessment and collision avoidance decision-making.
Keywords：autonomous vesselemergency collision avoidance scenaryT-APF algorithmE-APF algorithmTCPADCPA
Publication Date：2025-07-30
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：8( 100-107 )