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Human factors at sea: common patterns of error in groundings and collisions

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  • Carl Macrae

Abstract

This research aimed to identify and map the common patterns of human and organizational causes underlying two types of marine accident: groundings and collisions. Generalizing patterns of causality from relatively unique and individual accident events required a structured and exploratory analytical approach. Two complementary human factor analysis tools were employed to analyse a set of 30 detailed marine accident reports produced by the Australian Transport Safety Bureau. Common patterns of causality were identified for both groundings and collisions. Groundings commonly resulted from a failure to adequately plan a passage, coupled with either a problem locating the vessel, or communication problems on the bridge. Collisions often involved a fishing vessel and a bulk carrier or cargo vessel, and commonly resulted from both a problem identifying the existence or speed of the other vessel and, again, an inadequate planning process. Generalizing these common causal patterns from a number of accidents identifies a range of points at which crews, managers and policymakers can intervene to forestall the development of these accidents. The method developed here may also be productively extended and applied to other accident types and used as an ongoing risk management tool.

Suggested Citation

  • Carl Macrae, 2009. "Human factors at sea: common patterns of error in groundings and collisions," Maritime Policy & Management, Taylor & Francis Journals, vol. 36(1), pages 21-38, February.
    • Handle: RePEc:taf:marpmg:v:36:y:2009:i:1:p:21-38
    DOI: 10.1080/03088830802652262
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    Cited by:

    1. Lan, He & Ma, Xiaoxue & Ma, Laihao & Qiao, Weiliang, 2023. "Pattern investigation of total loss maritime accidents based on association rule mining," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    2. Özkan Uğurlu & Serdar Yıldız & Sean Loughney & Jin Wang & Shota Kuntchulia & Irakli Sharabidze, 2020. "Analyzing Collision, Grounding, and Sinking Accidents Occurring in the Black Sea Utilizing HFACS and Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 40(12), pages 2610-2638, December.
    3. Özkan Uğurlu & Serdar Kum & Yusuf Volkan Aydoğdu, 2017. "Analysis of occupational accidents encountered by deck cadets in maritime transportation," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(3), pages 304-322, April.
    4. Suyi Li & Qiang Meng & Xiaobo Qu, 2012. "An Overview of Maritime Waterway Quantitative Risk Assessment Models," Risk Analysis, John Wiley & Sons, vol. 32(3), pages 496-512, March.
    5. Bye, Rolf J. & Aalberg, Asbjørn L., 2018. "Maritime navigation accidents and risk indicators: An exploratory statistical analysis using AIS data and accident reports," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 174-186.
    6. Yishu Zheng & Wayne K. Talley & Di Jin & ManWo Ng, 2016. "Crew injuries in container vessel accidents," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(5), pages 541-551, July.
    7. Xiaolong Wang & Boling Zhang & Xu Zhao & Lulu Wang & Ruipeng Tong, 2020. "Exploring the Underlying Causes of Chinese Eastern Star, Korean Sewol, and Thai Phoenix Ferry Accidents by Employing the HFACS-MA," IJERPH, MDPI, vol. 17(11), pages 1-19, June.
    8. Birgit Pauksztat, 2017. "Effects of job demands and social interactions on fatigue in short sea cargo shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(5), pages 623-640, July.
    9. Yildiz, Serdar & Uğurlu, Özkan & Wang, Jin & Loughney, Sean, 2021. "Application of the HFACS-PV approach for identification of human and organizational factors (HOFs) influencing marine accidents," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    10. Valdez Banda, Osiris A. & Kannos, Sirpa & Goerlandt, Floris & van Gelder, Pieter H.A.J.M. & Bergström, Martin & Kujala, Pentti, 2019. "A systemic hazard analysis and management process for the concept design phase of an autonomous vessel," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    11. Heij, C. & Knapp, S., 2018. "Predictive power of inspection outcomes for future shipping accidents," Econometric Institute Research Papers EI2018-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Shiqi Fan & Zaili Yang & Eduardo Blanco-Davis & Jinfen Zhang & Xinping Yan, 2020. "Analysis of maritime transport accidents using Bayesian networks," Journal of Risk and Reliability, , vol. 234(3), pages 439-454, June.

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