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An Overview of Maritime Waterway Quantitative Risk Assessment Models

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  • Suyi Li
  • Qiang Meng
  • Xiaobo Qu

Abstract

The safe navigation of ships, especially in narrow shipping waterways, is of the utmost concern to researchers as well as maritime authorities. Many researchers and practitioners have conducted studies on risk assessment for maritime transportation and have proposed risk reduction/control measures accordingly. This article provides a detailed review and assessment of various quantitative risk assessment models for maritime waterways. Eighty‐seven academic papers and/or project reports are summarized and discussed. The review then proceeds to analyze the frequency and consequence estimation models separately. It should be pointed out that we further summarize the advantages and disadvantages of frequency estimation models and provide recommendations for their application. From the overview, we find that the quantification of the impact of human error is of great importance and should be considered in future studies. Possible solutions are also proposed in the discussions.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:riskan:v:32:y:2012:i:3:p:496-512
    DOI: 10.1111/j.1539-6924.2011.01697.x
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    8. Montewka, Jakub & Hinz, Tomasz & Kujala, Pentti & Matusiak, Jerzy, 2010. "Probability modelling of vessel collisions," Reliability Engineering and System Safety, Elsevier, vol. 95(5), pages 573-589.
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    2. Du, Lei & Goerlandt, Floris & Kujala, Pentti, 2020. "Review and analysis of methods for assessing maritime waterway risk based on non-accident critical events detected from AIS data," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    3. Aziz, Abdul & Ahmed, Salim & Khan, Faisal & Stack, Chris & Lind, Annes, 2019. "Operational risk assessment model for marine vessels," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 348-361.
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    5. Carine Dominguez-Péry & Lakshmi Narasimha Raju Vuddaraju & Isabelle Corbett-Etchevers & Rana Tassabehji, 2021. "Reducing maritime accidents in ships by tackling human error: a bibliometric review and research agenda," Journal of Shipping and Trade, Springer, vol. 6(1), pages 1-32, December.
    6. Eko Hariyadi Budiyanto & Raja Oloan Saut Gurning & Trika Pitana, 2021. "The Application of Business Impact Analysis Due to Electricity Disruption in a Container Terminal," Sustainability, MDPI, vol. 13(21), pages 1-17, October.
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    8. Montewka, Jakub & Manderbacka, Teemu & Ruponen, Pekka & Tompuri, Markus & Gil, Mateusz & Hirdaris, Spyros, 2022. "Accident susceptibility index for a passenger ship-a framework and case study," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    9. Zhang, Weibin & Feng, Xinyu & Goerlandt, Floris & Liu, Qing, 2020. "Towards a Convolutional Neural Network model for classifying regional ship collision risk levels for waterway risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    10. Liye Zhang & Hua Wang & Qiang Meng & Hongbin Xie, 2019. "Ship accident consequences and contributing factors analyses using ship accident investigation reports," Journal of Risk and Reliability, , vol. 233(1), pages 35-47, February.
    11. Ramos, M.A. & Thieme, Christoph A. & Utne, Ingrid B. & Mosleh, A., 2020. "Human-system concurrent task analysis for maritime autonomous surface ship operation and safety," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    12. Ung, S.T., 2021. "Navigation Risk estimation using a modified Bayesian Network modeling-a case study in Taiwan," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    13. Marcin Budzynski & Aneta Luczkiewicz & Jacek Szmaglinski, 2021. "Assessing the Risk in Urban Public Transport for Epidemiologic Factors," Energies, MDPI, vol. 14(15), pages 1-34, July.
    14. Xin, Xuri & Liu, Kezhong & Yang, Zaili & Zhang, Jinfen & Wu, Xiaolie, 2021. "A probabilistic risk approach for the collision detection of multi-ships under spatiotemporal movement uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Marcelo Ramos Martins & Marco Aurélio Pestana & Enrique Andrés López Droguett, 2020. "A Methodology for Assessing the Probability of Occurrence of Undesired Events in the Tietê–Paraná Inland Waterway Based on Expert Opinion," Risk Analysis, John Wiley & Sons, vol. 40(6), pages 1279-1301, June.
    16. Mazurek, J. & Lu, L. & Krata, P. & Montewka, J. & Krata, H. & Kujala, P., 2022. "An updated method identifying collision-prone locations for ships. A case study for oil tankers navigating in the Gulf of Finland," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    17. 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.
    18. Gino J. Lim & Jaeyoung Cho & Selim Bora & Taofeek Biobaku & Hamid Parsaei, 2018. "Models and computational algorithms for maritime risk analysis: a review," Annals of Operations Research, Springer, vol. 271(2), pages 765-786, December.
    19. Yamin Huang & P. H. A. J. M. van Gelder, 2020. "Time‐Varying Risk Measurement for Ship Collision Prevention," Risk Analysis, John Wiley & Sons, vol. 40(1), pages 24-42, January.

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