JACIII Vol.16 No.7 pp. 866-873
doi: 10.20965/jaciii.2012.p0866


Risk Assessment Model of Maritime Traffic in Time-Variant CPA Environments in Waterway

Jung Sik Jeong, Gyei-Kark Park, and Kwang Il Kim

Division of International Maritime Transportation Science, Mokpo National Maritime University, Mokpo City, Republic of Korea

August 1, 2012
October 30, 2012
November 20, 2012
closest point of approach (CPA), time to CPA (TCPA), collision probability, maritime traffic, risk assessment
This paper proposes a quantitative model for assessing collision risk for maritime traffic in waterways. The proposed method reflects recent maritime traffic characteristics under in time-variant CPA environments in waterways and models a dynamic causation factor as a risk indicator. To eliminate an uncertainty by human factors causing maritime accidents, the proposed model combines maritime accident statistics and weather records with spatial and temporal distribution determined on the basis of recent and real data for ship movements. Because our method reflects the characteristics of recent ship movements in the water area, it can be complementarily used with the conventional model using Bayesian Belief Network (BBN).
Cite this article as:
J. Jeong, G. Park, and K. Kim, “Risk Assessment Model of Maritime Traffic in Time-Variant CPA Environments in Waterway,” J. Adv. Comput. Intell. Intell. Inform., Vol.16 No.7, pp. 866-873, 2012.
Data files:
  1. [1] Y. Fujii, H. Yamanouchi, and T. Matui, “Survey on Vessel Traffic Management Systems and Brief Introduction to Marine Traffic Studies,” Electronic Navigation Research Institute Papers, No.45, pp. 39-41, 1984.
  2. [2] T.MacDuff, “The Probability of Vessel Collisions,” Ocean Industry, pp. 144-148, 1974.
  3. [3] P. Kujala, M. Hänninen, T. Arola, and J. Ylitalo, “Analysis of the marine traffic safety in the Gulf of Finland,” Reliability Engineering and System Safety, No.94, pp. 1349-1357, 2009.
  4. [4] J.Montewka, T. Hinz, P. Kujala, and J.Matusiak, “Probability modelling of vessel conditions,” Reliability Engineering and System Safety, No.95, pp. 573-589, 2010.
  5. [5] P. Friis-Hansen, “Basic Modelling Principles for Prediction of Collision and Grounding Frequencies,” IWRAPMKII, Rev.4, pp. 1-59, 2008.
  6. [6] P. Trucco, E. Cagno, F. Ruggeri, and O. Grande, “A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation,” Reliability Engineering and System Safety, No.93, pp. 823-834, 2008.
  7. [7] IALA, “IALA Risk Management Tool for Ports and Restricted Waterways,” 2nd ed., IALA Recommendation, O-134, pp. 1-22, 2009.
  8. [8] F. Goerlandt and P. Kujala, “Traffic simulation based ship collision probability modeling,” Reliability Engineering and System Safety, No.96, pp. 91-107, 2011.
  9. [9] J. M. Mou, C. van der Tak, and H. Ligteringen, “Study on collision avoidance in busy waterways by using AIS data,” Ocean Engineering, No.37, pp. 483-490, 2010.
  10. [10] IALS, “Vessel Traffic Services Manual,” 5th ed., pp. 40-47, 2012.
  11. [11] S. Kristiansen, “Maritime Transportation – Safety Management and risk Analysis,” Elsevier Butterworth-Heinemann, Burlington, pp. 163-167, 2005.
  12. [12] Y. Koldenhof, C. van der Tak, and C. C. Glansdorp, “Risk Awareness; a model to calculate the risk of a ship dynamically,” in the XIII Int. Scientific and Technical Conf. onMaritime Traffic Engineering, MTE09, 2009.
  13. [13] K. Inoue, K. Masuda, W. Sera, and H. Usui, “Guidelines to Assess the Safety of Marine Traffic-I, Evaluation of Ship-handling Difficulty based on the Environmental Stress Model,” J. of Japan Institute of Navigation, Vol.98, pp. 225-234, 1998.
  14. [14] N.-S. Son, I.-Y. Gong, S.-Y. Kim, and C.-M. Lee, “Study on the Estimation of Collision Risk of Ship in Ship Handling Simulator using Environmental Stress Model,” Proc. of Navigation and Port Research, Vol.28, No.2, pp. 73-80, 2004.

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