A quantitative method for the analysis of ship collision risk using AIS data

Abstract

Ship collision risk analysis is of great significance for maritime traffic management and surveillance in real operational conditions. However, the traditional concept of the closest point of approach (CPA) is limited, particularly in coastal areas. Thus, this paper introduces a quantitative analysis method for measuring ship collision risk. The proposed method uses both the static and dynamic information of Automatic Identification System (AIS) data. First, the closest points of ship-ship collision (CPC) are calculated based on the ship specifications (e.g., ship length and ship breadth) and the geographical positioning of ships. Dynamic ship collision boundaries are estimated via CPC for the involved ships. Then, a kinematics feature-based vessel conflict ranking operator (KF-VCRO) is introduced to evaluate ship collision risk by integrating the relative position vector and the relative velocity, accounting for static and dynamic information of AIS. Finally, our method is validated by simulating head-on, overtaking, and crossing situations, showing that it can accurately assess ship collision risk for typical ship collision scenarios. Especially, we further validated our proposed method through real-world experiments in Zhoushan, China. The results indicate that the proposed method provided accurate identification of high collision risk areas in Zhoushan in real maritime practices. It is concluded that (1) the method assists in quantifying ship collision risk and identifying high collision risk areas, and (2) estimating traffic risk provides further insight into maritime traffic surveillance.