Risk Analysis and Visualization of Merchant and Fishing Vessel Collisions in Coastal Waters: A Case Study of Fujian Coastal Area

Author:

Zhu Chuanguang12,Lei Jinyu123,Wang Zhiyuan124ORCID,Zheng Decai5,Yu Chengqiang2,Chen Mingzhong5,He Wei124ORCID

Affiliation:

1. School of Transportation, Fujian University of Technology, Fuzhou 350118, China

2. Fujian Engineering Research Center of Safety Control for Ship Intelligent Navigation, College of Physics and Electronic Information Engineering, Minjiang University, Fuzhou 350108, China

3. College of Computer and Data Science, Minjiang University, Fuzhou 350108, China

4. Fuzhou Institute of Oceanography, Minjiang University, Fuzhou 350108, China

5. Fuzhou Aids to Navigation Division of Eastern Navigation Services Center, China Maritime Safety Administration, Fuzhou 350004, China

Abstract

The invasion of ship domains stands out as a significant factor contributing to the risk of collisions during vessel navigation. However, there is a lack of research on the mechanisms underlying the collision risks specifically related to merchant and fishing vessels in coastal waters. This study proposes an assessment method for collision risks between merchant and fishing vessels in coastal waters and validates it through a comparative analysis through visualization. First of all, the operational status of fishing vessels is identified. Collaboratively working fishing vessels are treated as a unified entity, expanding their ship domain during operation to assess collision risks. Secondly, to quantify the collision risk between ships, a collision risk index (CRI) is proposed and visualized based on the severity of the collision risk. Finally, taking the high-risk area for merchant and fishing vessel collisions in the Minjiang River Estuary as an example, this paper conducts an analysis that involves classifying ship collision scenarios, extracts risk data under different collision scenarios, and visually analyzes areas prone to danger. The results indicate that this method effectively evaluates the severity of collision risk, and the identified high-risk areas resulting from the analysis are verified by the number of accidents that occurred in the most recent three years.

Funder

National Natural Science Foundation of China

Fujian Province Natural Science Foundation

Science and Technology Planning Project of Fuzhou

Fujian Province Key Science and Technology Innovation Project

Science and Technology Key Project of Fuzhou

Publisher

MDPI AG

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