CIPSO-Based Decision Support Method for Collision Avoidance of Super-Large Vessel in Port Waters

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Abstract
Effective and timely collision avoidance decision support is essential for super-large vessels navigating in port waters. To guarantee the navigational safety of super-large vessels, this work proposes a collision avoidance decision support method based on the curve increment strategy with adaptive particle swarm optimization (CIPSO). Firstly, the objective function is constructed based on the multi-objective optimization method. Here, a fuzzy comprehensive evaluation (FCE)-based vessel collision hazard model and vessel speed-varying energy-loss model integrating the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) are involved. Furthermore, in response to the limitations of the PSO algorithm, which is prone to falling into local optima in the later stages of iteration, a curve increment strategy is incorporated. To improve the performance of the global optimization, it is optimized using a local followed by global search method. The iterative evolution of CIPSO is used to obtain the optimal decision value in the set domain of feasible solutions. Finally, the effectiveness and feasibility of the proposed method are verified by the numerical simulation and large vessel maneuvering simulator, which can provide collision avoidance decision support for ship pilots.
Funding Information
  • National Natural Science Foundation of China (52171346, 2022KTSCX102)
  • Educational Science Planning Project of Guangdong Province (52171346, 2022KTSCX102)

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