Large Language Models in the Analysis of Radar Plotting Images in Accordance with COLREGs

The development of artificial intelligence (AI) opens new possibilities for the automatic interpretation of radar images in maritime navigation. Traditionally, the interpretation of radar indications requires the experience of the officer of the watch, who assesses the risk of collision and makes navigational decisions based on echo position, motion vectors, course, speed, Closest Point of Approach (CPA) and Time to Closest Point of Approach (TCPA). Systems using artificial intelligence can support this process through automatic object detection, tracking of their movement, classification of encounter situations, and indication of possible maneuvers in accordance with the Convention on the International Regulations for Preventing Collisions at Sea, 1972 (COLREGs). Maritime safety depends largely on the correct interpretation and application of the relevant COLREGs. The aim of this article is to present the capabilities, limitations and significance of generally available artificial intelligence tools like Large Language Models (LLMs) in the field of human–machine interaction. Attention is paid to the application of LLMs in radar plotting image analysis, the interpretation of navigational situations, and decision-making support from the perspective of marine traffic safety.