A path planning approach for ship collision avoidance integrating BRB reasoning and velocity obstacle algorithm - Minmin Zheng; Shuwu Wang; Haiyang Tu; Qianyu Lu (PLoS ONE, 2026)
Reliable path planning for ship collision avoidance remains challenging in complex maritime environments with dense traffic. This study proposes a novel approach that integrates Belief-Rule-Based (BRB) reasoning with the Velocity Obstacle (VO) algorithm for multi-ship encounter scenarios. First, the BRB framework groups ships with similar movement trends and close proximity, reducing both the number of avoidance targets and decision-making complexity. Based on the grouping results, the safety domain radius for individual ships and ship groups is set proportionally to ship length. Subsequently, the VO algorithm generates safe and feasible avoidance trajectories toward the goal. The method was tested in two scenarios, showing improved navigational safety and operational efficiency in congested waters. This work provides a foundation for intelligent decision-making in maritime safety management and supports sustainable development in the shipping industry.