Abstract:

To prevent collision accidents caused by ships failing to take timely and effective avoidance actions due to unclear situation awareness, an emergency ship maneuvering method aimed at addressing urgent dangerous threats was proposed. Based on the data from collision accident investigation reports, the ship encounter process was reconstructed. Considering the uncertainty and randomness of the ship collision risk, a bell-shaped grey cloud model was developed to obtain PCR in real-time and reveal its temporal evolution characteristics. The Kriging spatial interpolation algorithm was used to obtain the perception and graph representation of PCR between two ships. Furthermore, an avoidance decision-making assessment index was proposed to provide emergency maneuvering methods for steering collision avoidance. The validations of the collision accident in the crossing situation indicated that steering avoidance could effectively avoid a close-quarters situation if the give-way ship had taken action by the rudder in a crossing situation and turned starboard by 112.5° before the time of closest point of approach (TCPA) was 10 min. Furthermore, if the give-way ship did not take any action, the stand-on ship should turn to starboard by 45° before the TCPA was 4 min to effectively avoid immediate danger. This study proposes a fine-grained accident data-driven emergency ship-handling method that can be implemented in conjunction with traditional radar mapping and nautical experience ship-handling methods.

Key words: immediate danger, crossing situation, emergency ship maneuvering, gray-cloud model, potential collision risk(PCR)