Research on collaborative decision-making method for unmanned surface vehicle clusters in maritime security scenarios

Against the backdrop of intensifying maritime strategic competition and the profound transformation of maritime security paradigms, to address the emerging unmanned and clustered challenges in maritime security, this paper designs a collaborative decision-making framework for unmanned surface vehicle (USV) clusters in maritime security scenarios. The framework systematically constructs a complete process from threat assessment to mission execution: first, a multi-feature fusion model is employed to quantify target threat levels, and interception points are pre-calculated using the parallel approach method; then, for resource-constrained situations, a K-means algorithm incorporating outlier influence is applied to cluster and consolidate interception points effectively; in path planning, an improved particle swarm optimization algorithm with inertia decay and bow-direction constraints is utilized to generate smooth trajectories; afterwards, a market-based mechanism is adopted for task allocation, achieving dynamic negotiation and resource coordination. Finally, simulation experiments under typical maritime security scenarios are conducted; the results show that effective interception can be accomplished in both resource-sufficient and resource-deficient settings.