海上环境动态多变，在较小区域内船舰难以快速调整路径，增加航行碰撞风险。为此，提出小区域舰船航行局部避碰路径优化算法设计。构建船舰小区域内三自由度操纵函数，分析动力特性。采用并行化FP-Growth算法，设定分区核数实现并行运算，挖掘历史数据中的强关联规则作为初始可行路径集。深度融合当前的船舶动力特性模型，提出一种改进的人工势场法：在目标点与障碍物势场模型中，显式引入船舶操纵特性参数进行矢量合力计算与航向动态调整，确保生成的避碰路径符合船舶运动学约束。实验结果表明，该算法在小区域多种复杂工况下，均能显著提升小区域内路径优化效率，并稳定维持高安全系数0.95以上，为小区域舰船安全、高效航行提供了有效的技术支撑。
The dynamic and ever-changing marine environment makes it difficult for ships to quickly adjust their routes in small areas, increasing the risk of navigation collisions. Therefore, a local collision avoidance path optimization algorithm design for small area ship navigation is proposed. Construct a three degree of freedom control function within a small area of the ship and analyze its dynamic characteristics. Adopting the parallelized FP Growth algorithm, setting the number of partition cores to achieve parallel operations, and mining strong association rules in historical data as the initial feasible path set. Deeply integrating the current ship dynamic characteristic model, an improved artificial potential field method is proposed: in the target point and obstacle potential field model, ship maneuvering characteristic parameters are explicitly introduced for vector resultant force calculation and heading dynamic adjustment, ensuring that the generated collision avoidance path conforms to ship dynamics constraints. The experimental results show that the algorithm can significantly improve the efficiency of path optimization in small areas under various complex working conditions, and stably maintain a high safety factor of 0.95 or above, providing effective technical support for safe and efficient navigation of ships in small areas.
2026,48(4): 120-124 收稿日期：2025-8-28
DOI：10.3404/j.issn.1672-7649.2026.04.018
分类号：U675.9；TP391
基金项目：山西省高等学校科技创新计划创新平台项目（2022P018）
作者简介：王龙(1988-),男,硕士,副教授,研究方向为智能软件工程
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