Abstract
An intelligent ship collision avoidance mechanism based on improved swarm intelligence is presented. To expedite optimal decision-making system to prevent vessel collision, an adaptive brain storm optimization (ABSO) with variational inference-based expectation maximum for Mean-shift is proposed. The threshold for random update of individuals in brain storm optimization algorithm was adaptively renewed. The fitness was based on turning amplitude, and distance from original route. The proposed algorithm was tested under different scenarios of ship encounter, including crossing, head-on, and overtaking situations. The rationale is validated via typical cases. One of the minor objectives of the optimization was to prevent ships from steering to the side of the wind farm, which ensures the safety of navigation near offshore wind farm. This algorithm was used in collision avoidance near the offshore wind farm. Results show that calculations based on the proposed optimization method contribute to reasonable and effective decision-making.
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