Ships traffic encounter scenarios generation using sampling and clustering techniques

The Marine Autonomous Surface Ships (MASS) constitute a novel type of systems, which require novel methods for their design and safety assurance. The collision avoidance system is considered one of the most critical systems for MASS. This study aims at developing a process for generating and selecting ship encounter scenarios to test the collision avoidance system in a virtual environment. The proposed process employs sampling techniques for generating encounter scenarios, deterministic criteria for identifying the hazardous scenarios, risk metrics estimation for the classification of the encounter situations, as well as clustering techniques for further downsizing of the scenarios number. This process is applied to a small short-shipping vessel thus demonstrating its applicability