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An updated method identifying collision-prone locations for ships. A case study for oil tankers navigating in the Gulf of Finland

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Listed:
  • Mazurek, J.
  • Lu, L.
  • Krata, P.
  • Montewka, J.
  • Krata, H.
  • Kujala, P.

Abstract

To ensure the risk level associated with continuously increasing maritime traffic through particularly sensitive sea areas remains at acceptable level, a periodic risk assessment needs to be carried out by the relevant authorities. As a part of such assessment, allowing for proactive countermeasures to mitigate risk, the frequency of accidents is estimated along with the assessment of geographical locations where the accidents are most likely to happen.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:217:y:2022:i:c:s0951832021005330
    DOI: 10.1016/j.ress.2021.108024
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    Cited by:

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    2. Rong, H. & Teixeira, A.P. & Guedes Soares, C., 2024. "A framework for ship abnormal behaviour detection and classification using AIS data," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    3. Wang, Hong & Chen, Ning & Wu, Bing & Guedes Soares, C., 2024. "Human and organizational factors analysis of collision accidents between merchant ships and fishing vessels based on HFACS-BN model," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    4. Antão, P. & Sun, S. & Teixeira, A.P. & Guedes Soares, C., 2023. "Quantitative assessment of ship collision risk influencing factors from worldwide accident and fleet data," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    5. Puisa, Romanas & Montewka, Jakub & Krata, Przemyslaw, 2023. "A framework estimating the minimum sample size and margin of error for maritime quantitative risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Zhang, Mingyang & Zhang, Di & Fu, Shanshan & Kujala, Pentti & Hirdaris, Spyros, 2022. "A predictive analytics method for maritime traffic flow complexity estimation in inland waterways," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    7. Gil, Mateusz & Kozioł, Paweł & Wróbel, Krzysztof & Montewka, Jakub, 2022. "Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics," Reliability Engineering and System Safety, Elsevier, vol. 220(C).

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