Collision risk analysis on ferry ships in Jiangsu Section of the Yangtze River based on AIS data

• Published in: Reliability engineering & system safety Vol. 215; p. 107901
• Main Authors: Cai, Mingyou, Zhang, Jinfen, Zhang, Di, Yuan, Xiaoli, Soares, C. Guedes
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.11.2021; Elsevier BV
• Subjects: AIS data; Collision risk; Entropy; Ferries; Ferry ship; Inland waterway transportation; Navigation safety; Reliability engineering; Risk analysis; Risk assessment; Risk factors; Risk influencing factors; Rivers; Ships; Space debris; Yangtze River; AIS data; Ferry ship; Inland waterway transportation; Collision risk; Risk influencing factors
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2021.107901

•A quantitative assessment model on ferry collision risk is proposed.•The collision risk indexes are calculated using entropy theory.•The multi-ship encounters and ferry characteristics are considered.•Ferry collision risk is evaluated from both real-time and integrated perspectives. To assess the collision risk of ferries in the Yangtze River during crossing, the collision risk modeling is conducted based on AIS data. Risk Influencing Factors (RIFs) including Distance to Closest Point of Approach (DCPA), Time to Closest Point of Approach (TCPA), distance and relative velocity are involved. First, the historical multi-ship encounter scenarios involved ferry during crossing are identified from AIS data. Then, the value of RIFs is calculated according to their cumulative distribution, and their corresponding weights are determined using entropy theory. Next, the Collision Risk Index of Ferry (CRIF) is proposed considering the behavior of ferry and multiple target ships, which makes it possible to assess real-time collision risk during crossing and to integrate collision risk of each voyage based on historical encounter scenarios. The performance of the proposed model is evaluated according to the analysis on several encounter scenarios with different collision risk. Furthermore, the areas with higher collision risk are identified. The results bring some new insights to enhancing navigation safety of ferries.