使用COLREGs感知最优规划的船舶轨迹预测
Vessel Trajectory Prediction using COLREGs-aware Optimal Planning
- ABB Corporate Research（ABB企业研究部）
- Department of Electrical Engineering, Linköping University（Linköping大学电气工程系）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
研究船舶轨迹预测问题，核心方法是先利用A*搜索生成初始轨迹，再用数值优化器确保符合COLREG，以船舶当前位置、速度和目的地为输入，基于AIS数据验证，比基于学习的方法预测更快。
AI中文摘要：
本文提出一种基于最优规划的船舶轨迹预测方法。首先利用A*搜索生成考虑静态障碍物的粗略初始轨迹以提供可行的热启动。第二步，使用数值优化器确保符合《国际海上避碰规则》（COLREG）。预测问题从周围每艘船舶的角度被视为顺序轨迹规划，仅需其当前位置、速度和预期目的地作为输入。由于后者包含在AIS消息中，所以比通常需要更长数据历史的基于学习的方法预测更快。该方法通过由AIS数据构建的真实场景进行了验证。
英文摘要：
This paper presents a trajectory prediction method for marine vessels based on optimal planning. Crude initial trajectories respecting static obstacles are first generated using A*-search to provide a feasible warm start. In the second step, a numerical optimizer is used to ensure COLREG compliance. The prediction problem is posed as sequential trajectory planning from the perspective of each surrounding vessel, requiring only their current positions, velocities, and intended destinations as input. As the latter is included in AIS messages, this enables faster predictions than learning-based methods that typically require longer data histories. The proposed method is validated using real-world scenarios constructed from AIS data.
