Spatial-temporal analysis method of ship traffic accidents involving data field: An evidence from risk evolution of ship collision. (15th May 2023)

• Record Type: Journal Article
• Authors: Zhu, Qinghua; Xi, Yongtao; Hu, Shenping; Wu, Jianjun; Han, Bing
• Is Part Of: Ocean engineering. Volume 276(2023)
• Publication Date: 2023-05-15
• Subjects: Accident analysis -- Spatial-temporal characteristics -- Risk evolution -- Data field -- Collision risk -- Gaussian mixture clustering; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2023.114191
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Collision accident is the commonest type of ship traffic accident. Analysis of the spatial-temporal characteristics during the ship encounter process is helpful to the discovery of the accident evolution mechanism. The spatial-temporal analysis method was developed for collision accidents from maritime accident investigation reports to reveal the evolution characteristics of potential collision risk (PCR) during the two ships' encounters. First, a four-dimensional interpolation algorithm under the Radar window was proposed by analyzing the uncertainty of risk collision from different ship parameters. Second, a data field cognitive model with Gaussian mixture clustering on PCR was constructed according to the Radar information of the ship encounter process. Last but not least, combining different collision avoidance scenarios under the ship domain, the spatial-temporal characteristics of PCR were discussed to reveal the evolution mechanism. Empirical evidence shows that the laws of time are equivalent to space in the four stages of the ship encounter process. Ship's parameters make a difference in risk perception under the Radar window. Different encounter situations have significant impacts on Radar-based collision avoidance. Highlights: Spatial-temporal analysis method was developed for ship collision accidents from maritime accident investigation reports. Combining the four-dimensional interpolation algorithm into data field, Gaussian mixture clustering under Radar window was applied. Considering the asymmetry between ships and situations, about 4 minutes before the collision was the approaching demarcation point.