AIS data based identification of systematic collision risk for maritime intelligent transport system

Abstract

The identification of vessel collision risk for a Maritime Intelligent Transport System (MITS) is crucial for maritime safety and management. This paper considers the identification of the Systematic Collision Risk (SCR) for an MITS based on AIS data, which is obtained by wireless communication among vessels and between vessels and shore-based stations. SCR is modeled as a function of the collision risk of each vessel. A computing method for the SCR of a two-vessel case is proposed. Meanwhile, a hierarchical clustering based simplification algorithm is provided and applied to transform the topology of an MITS, thus simplifying the computing of the SCR. Based on the two-vessel case and transformation, a bottom-to-top weighted fusion method is employed to calculate the SCR for an MITS. Extensive numerical examples of simulative and real AIS data verify the effectiveness of our modeling and computing.