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Impact of voyage segments on maritime accidents: an analysis of navigational factors and accident causes

Impact of voyage segments on maritime accidents: an analysis of navigational factors and accident causes
Impact of voyage segments on maritime accidents: an analysis of navigational factors and accident causes

Maritime transportation, a cornerstone of global trade, faces significant risks from maritime accidents, which can result in severe human casualties, substantial property loss, and extensive environmental damage. This study aims to improve the understanding of how different voyage segments, coastal waters, open seas, and restricted waters, influence maritime accidents by systematically analysing navigational characteristics and Risk Influential Factors (RIFs) across segments. The study employs a Tree-Augmented Naïve Bayes (TAN) model to quantify the probabilistic influence of RIFs on accident occurrence, enabling the explicit modelling of interdependencies that traditional approaches fail to capture. Scenario analysis is further conducted to assess segment-specific accident patterns and to identify how operational, environmental, and human-centred factors vary across navigational contexts. The results reveal both shared and segment-unique root causes, as well as high-risk transition zones where accident likelihood changes markedly between segments. By integrating voyage-segment analysis with a TAN structure, this paper advances maritime accident modelling beyond prior applications and provides actionable insights for risk-informed decision-making. The findings support the optimisation of route planning, the design of segment-specific and transition-focused safety measures, and the development of more effective maritime safety management strategies across diverse operational environments.

Bayesian networks, Maritime accidents, Risk assessment, Scenario analysis, Voyage segments
0951-8320
Wu, Yiheng
0e074f4c-1ed4-4fdf-84e9-6ea1e8a3b1fd
Li, Huanhuan
5e806b21-10a7-465c-9db3-32e466ae42f1
Jiao, Hang
af70e929-ff8d-4020-92a5-34c55f6aba7c
Chen, Zhong Shuo
59533721-057c-40d4-92ee-e849e993b704
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
Yang, Zaili
82d4eebc-4532-4343-8555-35169e79bb6d
Wu, Yiheng
0e074f4c-1ed4-4fdf-84e9-6ea1e8a3b1fd
Li, Huanhuan
5e806b21-10a7-465c-9db3-32e466ae42f1
Jiao, Hang
af70e929-ff8d-4020-92a5-34c55f6aba7c
Chen, Zhong Shuo
59533721-057c-40d4-92ee-e849e993b704
Murphy, Alan J.
8e021dad-0c60-446b-a14e-cddd09d44626
Yang, Zaili
82d4eebc-4532-4343-8555-35169e79bb6d

Wu, Yiheng, Li, Huanhuan, Jiao, Hang, Chen, Zhong Shuo, Murphy, Alan J. and Yang, Zaili (2026) Impact of voyage segments on maritime accidents: an analysis of navigational factors and accident causes. Reliability Engineering & System Safety, 270, [112188]. (doi:10.1016/j.ress.2026.112188).

Record type: Article

Abstract

Maritime transportation, a cornerstone of global trade, faces significant risks from maritime accidents, which can result in severe human casualties, substantial property loss, and extensive environmental damage. This study aims to improve the understanding of how different voyage segments, coastal waters, open seas, and restricted waters, influence maritime accidents by systematically analysing navigational characteristics and Risk Influential Factors (RIFs) across segments. The study employs a Tree-Augmented Naïve Bayes (TAN) model to quantify the probabilistic influence of RIFs on accident occurrence, enabling the explicit modelling of interdependencies that traditional approaches fail to capture. Scenario analysis is further conducted to assess segment-specific accident patterns and to identify how operational, environmental, and human-centred factors vary across navigational contexts. The results reveal both shared and segment-unique root causes, as well as high-risk transition zones where accident likelihood changes markedly between segments. By integrating voyage-segment analysis with a TAN structure, this paper advances maritime accident modelling beyond prior applications and provides actionable insights for risk-informed decision-making. The findings support the optimisation of route planning, the design of segment-specific and transition-focused safety measures, and the development of more effective maritime safety management strategies across diverse operational environments.

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More information

Accepted/In Press date: 2 January 2026
e-pub ahead of print date: 2 January 2026
Published date: 7 January 2026
Keywords: Bayesian networks, Maritime accidents, Risk assessment, Scenario analysis, Voyage segments

Identifiers

Local EPrints ID: 509012
URI: http://eprints.soton.ac.uk/id/eprint/509012
ISSN: 0951-8320
PURE UUID: 668cd424-9e93-4dd7-8e4c-a28863ab7bd4
ORCID for Huanhuan Li: ORCID iD orcid.org/0000-0002-4293-4763

Catalogue record

Date deposited: 10 Feb 2026 17:34
Last modified: 11 Feb 2026 03:17

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Contributors

Author: Yiheng Wu
Author: Huanhuan Li ORCID iD
Author: Hang Jiao
Author: Zhong Shuo Chen
Author: Alan J. Murphy
Author: Zaili Yang

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