Dynamic adaptive autonomous navigation decision-making method in traffic separation scheme waters: A case study for Chengshanjiao waters

Abstract

A dynamic adaptive decision-making method in traffic separation scheme (TSS) waters (Chengshanjiao) was explored to achieve fully autonomous navigation. A static traffic environment comprising the digital models of the constituent parts of a TSS was established. A dynamic model was constructed using the target ships. Static and dynamic traffic environments serve as a foundation for decision-making. Based on the mathematical evaluations of the 1972 International Regulations for Preventing Collisions at Sea (COLREGs) and good seamanship, the requirements for motor-vessel collision avoidance in different scenarios and stages were presented. An automatic navigation method was established that could control the ship, automatically track the route, and assess the ship motion state. A collision risk identification model and dynamic collision avoidance mechanism for this type of water were built to identify the most dangerous target ship and a feasible manoeuvring plan to ensure safety in a multi-ship environment. To adapt to the random movement of target ships and correct residual errors, an autonomous navigation decision framework was proposed based on time-series rolling calculations. The ship safely moved through the water by altering its course 5° to starboard at 326 s, 6° to starboard at 887 s, route tracking at 1627 s, altering its course 6° to starboard at 4072 s, and route tracking at 4813 s in an experimental scenario with eight target ships. Six of the eight target ships were randomly manipulated. The results demonstrate that this decision-making technique can be utilised in practice and is precise to 1°.