The encounter situation between marine vessels determines how they should navigate to obey COLREGs, but time-varying and stochastic uncertainty in estimation of angles of encounter, and of closest point of approach, easily give rise to different assessment of situation at two approaching vessels. This may lead to high-risk conditions and could cause collision. This article considers decision making under uncertainty and suggests a novel method for probabilistic interpretation of vessel encounters that is explainable and provides a measure of uncertainty in the evaluation. The method is equally useful for decision support on a manned bridge as on Marine Autonomous Surface Ships (MASS) where it provides input for automated navigation. The method makes formal safety assessment and validation feasible. We obtain a resilient algorithm for machine interpretation of COLREGs under uncertainty and show its efficacy by simulations.

翻译：海上船舶之间的相遇情形决定了它们应如何遵守《国际海上避碰规则》（COLREGs）进行航行，但相遇角度和最近会遇点估计中存在的时变随机不确定性，容易导致两艘接近船舶对情势产生不同判断。这可能引发高风险状况并导致碰撞。本文研究了不确定性条件下的决策制定，提出了一种新颖的船舶相遇概率解释方法，该方法具有可解释性，并能提供评估中的不确定性度量。该算法既适用于有人驾驶船舶的决策支持，也适用于海洋自主水面舰船（MASS）的自主导航输入。该方法使得形式化安全评估与验证成为可能。我们获得了一种在不确定性条件下实现COLREGs机器解释的鲁棒算法，并通过仿真验证了其有效性。