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Probabilistic risk analysis for ship-ship collision: State-of-the-art

Published on Aug 1, 2019in Safety Science3.619
· DOI :10.1016/j.ssci.2019.04.014
Pengfei Chen3
Estimated H-index: 3
(TU Delft: Delft University of Technology),
Yamin Huang6
Estimated H-index: 6
(TU Delft: Delft University of Technology)
+ 1 AuthorsP.H.A.J.M. van Gelder22
Estimated H-index: 22
(TU Delft: Delft University of Technology)
Source
Abstract
Abstract Maritime transportation system has made a significant contribution to the development of the world economy. However, with the growth of quantity, scale, and speed of ships, maritime accidents still pose incrementing risk to individuals and societies in terms of multiple aspects, especially collision accidents between ships. Great effort is needed to prevent the occurrence of such accidents and to improve navigational safety and traffic efficiency. In this paper, extensive literature on probabilistic risk analysis on ship-ship collision was collected and reviewed focusing on the stakeholders which may benefit from the research and the methodologies and criteria adopted for collision risk. The paper identifies stakeholders, the modelling aspects (frequency estimation, causation analysis, etc.) in which the stakeholders are interested in. A classification system is presented based on the technical characteristics of the methods, followed by detailed descriptions of representative approaches and discussion. Areas for improvement of such risk analysis approaches are highlighted, i.e. identifying collision candidates, assessing the collision probability of multiple ships encounters, assessing the human and organizational factors. Three findings are concluded from this literature review: (1) Research on collision risk analysis and evaluation of ship encounters from individual ship perspective have facilitated the research in macroscopic perspective, and in turn, results from macroscopic research can also facilitate individual risk analysis by providing regional risk characteristics; (2) Current approaches usually estimate geometric probability by analysing data at certain intervals, which could lead to over/underestimation of the results; and (3) For causation probability induced by human and organisational factors in collision accidents, lack of data and uncertainty is still a problem to obtain accurate and reliable estimations. The paper also includes a discussion with respect to the applicability of the methods and outlines further work for improvement. The results in this paper are presented in a systematic structure and are formulated in a conclusive manner. This work can potentially contribute to developing better risk models and therefore better maritime transportation systems.
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