Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-24T23:25:05.915Z Has data issue: false hasContentIssue false

Assessing Grounding Frequency using Ship Traffic and Waterway Complexity

Published online by Cambridge University Press:  07 August 2014

Arsham Mazaheri*
Affiliation:
(Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology, P.O. Box 12200, FI-00076 AALTO, Espoo, Finland)
Jakub Montewka
Affiliation:
(Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology, P.O. Box 12200, FI-00076 AALTO, Espoo, Finland)
Pentti Kotilainen
Affiliation:
(Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology, P.O. Box 12200, FI-00076 AALTO, Espoo, Finland)
Otto-Ville Edvard Sormunen
Affiliation:
(Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology, P.O. Box 12200, FI-00076 AALTO, Espoo, Finland)
Pentti Kujala
Affiliation:
(Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology, P.O. Box 12200, FI-00076 AALTO, Espoo, Finland)
*

Abstract

Ship traffic is the factor that presents in almost all of the existing grounding risk models. It is considered to be one of the main factors affecting the expected frequency of ship groundings. This is mostly accepted by experts as common sense. However, there is no research available on the actual dependency between ship traffic and grounding accidents. In this paper, we conduct a study aimed at determining the statistical dependency between the density and distribution of traffic, the number and frequency of grounding accidents and the dependency between the complexity of waterways and an actual accident. For this purpose we utilise statistical analysis of maritime traffic, obtained from Automatic Identification System (AIS) data and grounding accidents, enhanced with the expert elicitation techniques delivering the waterway complexity index. The sea area under investigation is the Gulf of Finland. The results show statistical dependency between frequency of grounding and waterway complexity as well as the traffic distribution. However, the study does not reveal any significant dependency between grounding and traffic density.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Akhtar, M.J. and Utne, I.B. (2014). Human Fatigue's Effect on The Risk of Maritime Groundings – A Bayesian Network Modeling Approach. Safety Science, 62, 427440.Google Scholar
Amrozowicz, M.D., Brown, A. and Golay, M. (1997). A Probabilistic Analysis of Tanker Groundings. 7th International Offshore and Polar Engineering Conference. Honolulu, Hawaii.Google Scholar
Briggs, M.J., Borgman, L.E. and Bratteland, E. (2003). Probability Assessment for Deep-Draft Navigation Channel Design. Coastal Engineering, 48, 2950.Google Scholar
Brown, A. and Haugene, B. (1998). Assessing the Impact of Management and Organizational Factors on the Risk of Tanker Grounding. 8th International Offshore and Polar Engineering Conference.Google Scholar
Fowler, T.G. and Sørgård, E. (2000). Modelling Ship Transportation Risk. Risk Analysis, 20, 225244.Google Scholar
Fujii, Y., Oshima, R., Yamanouchi, H. and Mizuki, N. (1974). Some Factors Affecting The Frequency Of Accidents In Marine Traffic: I- The Diameter Of Evasion For Crossing Encounters, II- The Probability Of Stranding, III- The Effect Of Darkness On The Probability Of Collision And Stranding. The Journal of Navigation, 27, 239247.Google Scholar
Goerlandt, F. and Kujala, P. (2011). Traffic Simulation Based Ship Collision Probability Modeling. Reliability Engineering and System Safety, 96, 91107.Google Scholar
Goerlandt, F. and Kujala, P. (2014). On the reliability and validity of ship–ship collision risk analysis in light of different perspectives on risk. Safety Science, 62, 348365.Google Scholar
Goerlandt, F., Montewka, J., Kujala, P. (2014). Tools for an Extended Risk Assessment for Ropax Ship-Ship Collision. Vulnerability, Uncertainty, and Risk, 22922302, doi: 10.1061/9780784413609.230.Google Scholar
Hänninen, M., Mazaheri, A., Kujala, P., Montewka, J., Laaksonen, P., Salmiovirta, M., Klang, M. (2014). Expert elicitation of a navigation service implementation effects on ship groundings and collision in the Gulf of Finland. Proceedings of the Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, 228, 1928.Google Scholar
Hänninen, M., Valdez Banda, O., Kujala, P. (2014a). Bayesian network model of maritime safety management. Expert Systems with Applications, DOI: 10.1016/j.eswa.2014.06.029.Google Scholar
HELCOM. (2011). Report On Shipping Accidents In The Baltic Sea Area During 2011. Helsinki Commission, Baltic Marine Environment, Protection Commission.Google Scholar
Jebsen, J.J. and Papakonstantinou, V. C. (1997). Evaluation of The Physical Risk Of Ship Grounding; Department of Ocean Engineering. Massachusetts Institute of Technology.Google Scholar
Kite-Powell, H.L., Jin, D., Jebsen, J., Papakonstantinou, V. and Patrikalakis, N. (1999). Investigation of Potential Risk Factors for Groundings of Commercial Vessels in U.S. Ports. International Journal of Offshore and Polar Engineering, 9, 1621.Google Scholar
Kujala, P., Hänninen, M., Arola, T. and Ylitalo, J. (2009). Analysis of the Marine Traffic Safety in The Gulf of Finland. Reliability Engineering and System Safety, 94, 13491357.Google Scholar
Kuronen, J., Helminen, R., Lehikoinen, A. and Tapaninen, U. (2008). Maritime Transportation in the Gulf of Finland in 2007 and in 2015. University of Turku.Google Scholar
Lehman, A. (2005). JMP for Basic Univariate and Multivariate Statistics : A Step-by-Step Guide, Cary, NC, USA, SAS Press.Google Scholar
Lin, S.-C. (1999). Physical Risk Analysis of Ship Grounding. Massachusetts Institute of Technology.Google Scholar
Martins, M.R. and Maturana, M.C. (2010). Human Error Contribution in Collision and Grounding of Oil Tankers. Risk Analysis, 30, 674698.Google Scholar
Mazaheri, A., Montewka, J. and Kujala, P. (2013). Modelling the Risk of Ship Grounding – A Literature Review from a Risk Management Perspective. Published Online In Wmu Journal Of Maritime Affairs; doi: 10.1007/S13437-013-0056-3.Google Scholar
Mazaheri, A. and Ylitalo, J. (2010). Comments on Geometrical Modeling of Ship Grounding. 5th International Conference on Collision and Grounding of Ships (ICCGS). Espoo, Finland.Google Scholar
Montewka, J., Hinz, T., Kujala, P. and Matusiak, J. (2010). Probability Modelling of Vessel Collisions. Reliability Engineering and System Safety, 95, 573589.Google Scholar
Montewka, J., Krata, P., Goerlandt, F., Mazaheri, A. and Kujala, P. (2011). Marine Traffic Risk Modelling – An Innovative Approach and a Case Study. Proceedings of The Institution of Mechanical Engineers, Part O, Journal of Risk and Reliability, 225, 307322.Google Scholar
Montewka, J., Goerlandt, F., Kujala, P. (2014). On a systematic perspective on risk for formal safety assessment (FSA). Reliability Engineering & System Safety, 127, 7785.Google Scholar
Montewka, J., Ehlers, S., Goerlandt, F., Hinz, T., Tabri, K., Kujala, P. (2014a). A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels. Reliability Engineering & System Safety, 124, 142157.Google Scholar
MSC. (2003). Mandatory Ship Reporting Systems, SN/Circ.225. In IMO.Google Scholar
MSC. (2006). Mandatory Ship Reporting Systems, SN.1/Circ.258. In IMO.Google Scholar
O'hagan, A., Buck, C.E., Daneshkhah, A., Eiser, J.R., Garthwaite, P.H., Jenkinson, D.J., Oakley, J.E. and Rakow, T. (2006). Uncertain Judgements: Eliciting Experts' Probabilities, New York, John Wiley & Sons.Google Scholar
Otto, S., Pedersen, P.T., Samuelides, M. and Sames, P.C. (2002). Elements Of Risk Analysis For Collision And Grounding of a Ro-Ro Passenger Ferry. Marine Structures, 15, 461474.Google Scholar
Pedersen, P.T. (1995). Collision and Grounding Mechanics. Proceedings of WEMT ‘95’. Copenhagen, Denmark, The Danish Society of Naval Architecture and Marine Engineering.Google Scholar
Peng, H., Long, F. and Ding, C. (2005). Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, 12261238.Google Scholar
Praetorius, G. (2012). Safety within the Vessel Traffic Service (VTS) Domain – Understanding the Role of The VTS for Safety within Maritime Traffic Management, Licentiate Thesis, Department of Shipping and Marine Technology. Gothenburg, Chalmers University of Technology.Google Scholar
Quy, N.M., Vrijling, J.K., Gelder, P.H.A.J.M.V. and Groenveld, R. (2006). On the Assessment of Ship Grounding Risk in Restricted Channels. The 8th International Conference on Marine Sciences and Technologies – Black Sea Conference. Varna, Bulgaria.Google Scholar
Robson, C. (2008). How to do a Research Project, Singapore, Blackwell Publishing.Google Scholar
Samuelides, M.S., Ventikos, N.P. and Gemelos, I.C. (2009). Survey on Grounding Incidents: Statistical Analysis and Risk Assessment. Ships and Offshore Structures, 4, 5568.Google Scholar
Sonninen, S., Nuutinen, M. and Rosqvist, T. (2008). Development Process of The Gulf of Finland Mandatory Ship Reporting System, 614, VTT.Google Scholar
Sormunen, O-V.E., Goerlandt, F., Häkkinen, J., Posti, A., Hänninen, M., Montewka, J., Stahlberg, K., Kujala, P. (2014). Uncertainty in maritime risk analysis: Extended case study on chemical tanker collisions. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment doi: 10.1177/1475090213515640.Google Scholar
Steuer, R., Kurths, J., Daub, C.O., Weise, J. and Selbig, J. (2002). The Mutual Information: Detecting and Evaluating Dependencies Between Variables. Bioinformatics, 18, 231240.Google Scholar
Theil, H. (1970). On the estimation of relationships involving qualitative variables. American Journal of Sociology, 76, 103154.Google Scholar
van Dorp, J.R. and Merrick, J.R.W. (2009). On a Risk Management Analysis of Oil Spill Risk Using Maritime Transportation System Simulation. Annals of Operations Research, 129.Google Scholar