  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.
