Stochastic COLREGs Evaluation for Safe Navigation under Uncertainty

TL;DR

This paper introduces a probabilistic method for evaluating vessel encounters under uncertainty, enhancing safety and decision-making for both manned and autonomous ships by providing explainable assessments and uncertainty measures.

Contribution

It proposes a novel, explainable probabilistic approach for COLREGs evaluation that accounts for stochastic uncertainties, improving safety assessments and decision support for maritime navigation.

Findings

Method effectively handles stochastic uncertainties in vessel encounter assessments.

Simulations demonstrate improved safety and decision support capabilities.

Provides a formal framework for safety validation under uncertainty.

Abstract

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.