Anticipation of ship behaviours in multi-vessel scenarios
Dimitrios Papageorgiou, Peter Nicholas Hansen, Kjeld Dittmann, Mogens Blanke
Abstract
Highly reliable situation awareness is a main driver to enhance safety via autonomous technology in the marine industry. Groundings, ship collisions and collisions with bridges illustrate the need for enhanced safety. Authority for a computer to suggest actions or to take command, would be able to avoid some accidents where human misjudgement was a core reason. Autonomous situation awareness need be conducted with extreme confidence to let a computer algorithm take command. The anticipation of how a situation can develop is by far the most difficult step in situation awareness, and anticipation is the subject of this article. The IMO International Regulations for Preventing Collisions at Sea (COLREGS), describe the regulatory behaviours of marine vessels relative to each other, and correct interpretation of situations is instrumental to safe navigation. Based on a breakdown of COLREGS rules, this article presents a framework to represent manoeuvring behaviours that are expected when all vessels obey the rules. The article shows how nested finite automata can segregate situation assessment from decision making and provide a testable and repeatable algorithm. The suggested method makes it possible to anticipate own ship and other vessels’ manoeuvring in a multi-vessel scenario. The framework is validated using scenarios from a full-mission simulator.