Hostname: page-component-5b777bbd6c-w6wnr Total loading time: 0 Render date: 2025-06-21T16:47:24.263Z Has data issue: false hasContentIssue false
  • English
  • Français

A study on the relationships between factors contributing to fishing vessel collision accidents and hull damage severity in South Korea

Published online by Cambridge University Press:  23 May 2025

Hyungoo Park Open the ORCID record for Hyungoo Park [Opens in a new window] ,
Young-Soo Park ,
Sangwon Park Open the ORCID record for Sangwon Park [Opens in a new window] ,
Dae-Yul Chong ,
Wonsik Kang  and
Daewon Kim
Hyungoo Park
Affiliation:
Division of Navigation Convergence Studies, National Korea Maritime and Ocean University, Busan, South Korea
Young-Soo Park*
Affiliation:
Division of Navigation Convergence Studies, National Korea Maritime and Ocean University, Busan, South Korea
Sangwon Park
Affiliation:
Department of Maritime Police Science, Chonnam National University, Yeosu, South Korea
Dae-Yul Chong
Affiliation:
Korea Institute of Maritime and Fisheries Technology, Busan, South Korea.
Wonsik Kang
Affiliation:
Department of Marine Industry and Maritime Police, Jeju National University, Jeju, South Korea
Daewon Kim
Affiliation:
Division of Navigation Convergence Studies, National Korea Maritime and Ocean University, Busan, South Korea
*
Corresponding author: Young-Soo Park; Email: youngsoo@kmou.ac.kr
Get access Rights & Permissions [Opens in a new window]

Abstract

Among maritime accidents, fishing vessel collisions are particularly prone to both high frequency and severity. This study aims to identify the correlation between effective collision speed (Delta-V) and the severity of hull damage in fishing vessel collisions. Using data from collisions in South Korea, the study examines the influence of collision-related factors including Delta-V, collision location, collision subject, collision angle and the hull material of the impacted vessel on the extent of vessel damage. Statistical analyses and binary logistic regression were employed to assess trends and relationships between these variables. The findings confirm direct associations between hull damage severity and factors such as tonnage, collision location, the striking vessel and the extent of hull damage.

Keywords

Correlationmarine trafficnavigationship collision
Type
Research Article
Information
The Journal of Navigation , First View , pp. 1 - 21
Check for updates
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Antão, P., Sun, S., Teixeira, A. P. and Soares, C. G. (2023). Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data. Reliability Engineering & System Safety, 234, 109166.CrossRefGoogle Scholar
Chou, C. C., Li, R. F., Su, Y. L., Tsai, C. L. and Chang, K. Y. (2018). A study of the distribution of marine incidents in the harbours and waters surrounding Taiwan. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 233(3), 809–824.Google Scholar
Choiron, M. A., Setyarini, P. H. and Nurwahyudy, A. (2024). Fishing vessel safety in Indonesia: A study of accident characteristics and prevention strategies. International Journal of Safety & Security Engineering, 14(2), 499–511.CrossRefGoogle Scholar
Creative Composites Group (2023). Comparison of FRP against steel and aluminum. https://www.creativecompositesgroup.com/blog/frp-composites-vs.-steel-why-composites-come-out-on-top. Accessed 1 December 2023.Google Scholar
Eyres, D. J. and Bruce, G. J. (2012). Ship Construction. Elsevier, 73–74.Google Scholar
Fiskin, R., Cakir, E. and Sevgili, C. (2021). Decision tree and logistic regression analysis to explore factors contributing to harbour tugboat accidents. The Journal of Navigation, 74, 79–104.CrossRefGoogle Scholar
Hosmer, D. W. and Lemeshow, S. (1989). Applied Logistic Regression. John Wiley & Sons.Google Scholar
International Maritime Organization (IMO). (2008). RESOLUTION MSC.255(84).Google Scholar
International Organization for Standardization (ISO). (2009). ISO Guide 73:2009.Google Scholar
Kao, S. L. and Chang, K. Y. (2017). Study on fuzzy GIS for navigation safety of fishing boats. Journal of Marine Engineering & Technology, 16 (2), 84–93.CrossRefGoogle Scholar
Kim, H., Koo, K., Lim, H., Kwon, S. and Lee, Y. (2024). Analysis of Fishing Vessel Accidents and Suggestions for Safety Policy in South Korea from 2018 to 2022. Sustainability, 16 (9), 3537.CrossRefGoogle Scholar
Korea Maritime Safety Tribunal (KMST). (2018). Tanker 15 Myeong-jin, Fishery Boat Sunchang No. 1 Collision Safety Investigation Report.Google Scholar
Korea Maritime Safety Tribunal (KMST). (2020). Marine Safety Investigation Report on Collision between the M/V HANYU EMPIRE and F/V DAESUNG.Google Scholar
Korea Maritime Safety Tribunal (KMST). (2023). 2022 Maritime Accident Statistics, 42–159.Google Scholar
Lee, M. K. and Park, Y. S. (2020). Collision prevention algorithm for fishing vessels using mmWAVE communication. Journal of Marine Science and Engineering, 8 (2), 115.CrossRefGoogle Scholar
Lee, M. K., Park, Y. S., Park, S., Lee, E., Park, M. and Kim, N. E. (2021). Application of collision warning algorithm alarm in fishing vessel’s waterway. Applied Sciences, 11 (10), 4479.CrossRefGoogle Scholar
Lee, M. K., Park, Y. S. and Kang, W. S. (2019). A study on construction of collision prevention algorithm for small vessel using WAVE communication system. Journal of the Korean Society of Marine Environment and Safety, 25, 1–8.CrossRefGoogle Scholar
Ministry of Ocean and Fisheries (2020). Korea Design Standard. https://kpcs.portcals.go.kr/kc/selectKcListVw.do?docGubun=KDS. Accessed 1 December 2023.Google Scholar
Paik, J. K. and Pedersen, P. T. (1996). Modelling of the internal mechanics in ship collisions. Ocean Engineering, 23, 107–142.CrossRefGoogle Scholar
Park, H. G., Park, Y. S. and Park, S. W. (2023). A study on the correlation between effective impact speed and the severity of collision accidents with fishing vessels. Korean Journal of Navigation and Port Research, 47, 202–211.Google Scholar
Subash, T. D., Pradeep, A. S., Joseph, A. R., Jacob, A. and Jayaraj, P. S. (2020). Intelligent Collision Avoidance system for fishing boat. Materials Today: Proceedings, 24, 2457–2463.Google Scholar
Uğurlu, F., Yıldız, S., Boran, M., Uğurlu, Ö. and Wang, J. (2020). Analysis of fishing vessel accidents with Bayesian network and Chi-square methods. Ocean Engineering, 198, 106956.CrossRefGoogle Scholar
Wang, C., Corbett, J. J. and Firestone, J. (2007). Modeling energy use and emissions from North American shipping: Application of the ship traffic, energy, and environment model. Environmental Science & Technology, 41, 3226–3232.CrossRefGoogle ScholarPubMed
Wang, F., Du, W., Feng, H., Ye, Y., Grifoll, M., Liu, G. and Zheng, P. (2023). Identification of risk influential factors for fishing vessel accidents using claims data from fishery mutual insurance association. Sustainability, 15 (18), 13427.CrossRefGoogle Scholar
Weng, J., Ge, Y. E. and Han, H. (2016). Evaluation of shipping accident casualties using zero-inflated negative binomial regression technique. The Journal of Navigation, 69, 433–448.CrossRefGoogle Scholar
Weng, J. and Li, G. (2020). Economic loss analysis of fishing boat collisions considering spatial-temporal interaction effects. The Journal of Navigation, 73, 1069–1086.CrossRefGoogle Scholar
Weng, J., Li, G., Chai, T. and Yang, D. (2018). Evaluation of two-ship collision severity using ordered probit approaches. The Journal of Navigation, 71, 822–836.CrossRefGoogle Scholar
Yang, J., Sun, Y., Song, Q. and Ma, L. (2023). Laws and preventive methods of collision accidents between merchant and fishing vessels in coastal area of China. Ocean & Coastal Management, 231, 106404.CrossRefGoogle Scholar
Zhang, Y., Sun, X., Chen, J. and Cheng, C. (2021). Spatial patterns and characteristics of global maritime accidents. Reliability Engineering & System Safety, 206, 107310.CrossRefGoogle Scholar