Ship predictive collision avoidance method based on an improved beetle antennae search algorithm

Abstract

To enhance the real-time performance and reliability of existing ship collision avoidance methods by collision risk prediction, a predictive collision avoidance method based on an improved beetle antennae search (BAS) algorithm for underactuated surface vessels is proposed. Firstly, a simplified 3-DOF hydrodynamic model based on Abkowitz model is proposed, which provides a model basis for real-time prediction of ship states and collision risks. Referring to the idea of model predictive control (MPC), a predictive optimization strategy for real-time collision avoidance is established by minimizing the safety cost and the economic cost, i.e., collision risk and control changes at the same time. Specifically, the proposed simplified 3-DOF model is used as the state predictive model and the International Regulations for Preventing Collisions at Sea (COLREGs) is considered as the control constraints. To solve the optimization problem, an improved BAS algorithm is proposed to enhance the optimization performance of the original BAS algorithm under the known constraints, which is applied to solve the predictive collision avoidance problem. Simulation experiments under several typical encounter scenarios are carried out based on KVLCC2 ship model, and the effectiveness of the improved BAS based predictive collision avoidance method is verified.