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Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China

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  • Wang, Likun
  • Yang, Zaili

Abstract

The rapid development of the shipping industry requires the use of large vessels carrying high-volume cargoes. Accidents incurred by these vessels can lead to a heavy loss of life and damage to the environment and property. As a leading country in international trade, China has developed its waterway transport systems, including inland waterways and coastal shipping, in the past decades. A few catastrophic shipping accidents have occurred during this period. This paper aims to develop a new risk analysis approach based on Bayesian networks (BNs) to enable the analysis of accident severity in waterborne transportation. Although the risk data are derived from accidents that occurred in China's waters, the risk factors influencing accident severity and the risk modelling methodology are generic and capable of generating useful insights on waterway risk analysis in a broad sense.

Suggested Citation

  • Wang, Likun & Yang, Zaili, 2018. "Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 277-289.
    • Handle: RePEc:eee:reensy:v:180:y:2018:i:c:p:277-289
    DOI: 10.1016/j.ress.2018.07.021
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    References listed on IDEAS

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    1. Z. L. Yang & J. Wang & K. X. Li, 2013. "Maritime safety analysis in retrospect," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(3), pages 261-277, May.
    2. Di Zhang & Xinping Yan & Zaili Yang & Jin Wang, 2014. "An accident data–based approach for congestion risk assessment of inland waterways: A Yangtze River case," Journal of Risk and Reliability, , vol. 228(2), pages 176-188, April.
    3. Pristrom, Sascha & Yang, Zaili & Wang, Jin & Yan, Xinping, 2016. "A novel flexible model for piracy and robbery assessment of merchant ship operations," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 196-211.
    4. Trucco, P. & Cagno, E. & Ruggeri, F. & Grande, O., 2008. "A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 845-856.
    5. Bing Wu & Xinping Yan & Yang Wang & C. Guedes Soares, 2017. "An Evidential Reasoning‐Based CREAM to Human Reliability Analysis in Maritime Accident Process," Risk Analysis, John Wiley & Sons, vol. 37(10), pages 1936-1957, October.
    6. Hänninen, Maria & Kujala, Pentti, 2012. "Influences of variables on ship collision probability in a Bayesian belief network model," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 27-40.
    7. Cariou, Pierre & Mejia Jr., Maximo Q. & Wolff, Francois-Charles, 2008. "On the effectiveness of port state control inspections," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(3), pages 491-503, May.
    8. Jinfen Zhang & Ângelo P Teixeira & C. Guedes Soares & Xinping Yan & Kezhong Liu, 2016. "Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks," Risk Analysis, John Wiley & Sons, vol. 36(6), pages 1171-1187, June.
    9. Tzannatos, Ernestos & Kokotos, Dimitris, 2009. "Analysis of accidents in Greek shipping during the pre- and post-ISM period," Marine Policy, Elsevier, vol. 33(4), pages 679-684, July.
    10. Antão, Pedro & Guedes Soares, C., 2008. "Causal factors in accidents of high-speed craft and conventional ocean-going vessels," Reliability Engineering and System Safety, Elsevier, vol. 93(9), pages 1292-1304.
    11. Sotiralis, P. & Ventikos, N.P. & Hamann, R. & Golyshev, P. & Teixeira, A.P., 2016. "Incorporation of human factors into ship collision risk models focusing on human centred design aspects," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 210-227.
    12. Bhattacharya, Syamantak, 2012. "The effectiveness of the ISM Code: A qualitative enquiry," Marine Policy, Elsevier, vol. 36(2), pages 528-535.
    13. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    14. Zhang, D. & Yan, X.P. & Yang, Z.L. & Wall, A. & Wang, J., 2013. "Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 93-105.
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