Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-27T11:24:33.940Z Has data issue: false hasContentIssue false

Vessel Collision Frequency Estimation in the Singapore Strait

Published online by Cambridge University Press:  12 March 2012

Jinxian Weng
Affiliation:
(Department of Civil and Environmental Engineering, National University of Singapore) (Centre for Maritime Studies, National University of Singapore)
Qiang Meng*
Affiliation:
(Department of Civil and Environmental Engineering, National University of Singapore)
Xiaobo Qu
Affiliation:
(Department of Civil and Environmental Engineering, National University of Singapore)
*

Abstract

This paper aims to estimate Vessel Collision Frequency in the Singapore Strait. This frequency is obtained as the product of the number of Vessel Conflicts and the causation probability using the real-time vessel movement data from the Lloyd's Marine Intelligence Unit (Lloyd's MIU) database. The results show that the container carriers have the highest Vessel Collision Frequency while Roll-On Roll-Off (RORO) and passenger ships have the lowest frequency. Tankers cause the highest head-on collision frequency. In the Singapore Strait, the most risky overtaking area is between longitudes 103°48′E and 104°12′E. The most risky head-on area is between longitudes 103°50′E and 104°00′E while the majority of crossing collisions occur between longitudes 103°50′E and 104°12′E. The Vessel Collision Frequency is found to be 1·75 per year in the traffic lanes. Currently, westbound traffic in the Strait is more risky than eastbound traffic (the number of westbound collisions in July was 0·0991 while the number of eastbound collisions was 0·0470). Furthermore, the estimated Vessel Collision Frequency during the day is less than that at night. The results of this paper could be beneficial for the Maritime and Port Authority of Singapore to further enhance the navigational safety strategies implemented in the Singapore Strait.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2012

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

COWI, (2008). Risk Analysis of Sea Traffic in the Area Around Bornholm. Kongens Lyngby, Denmark: COWI A/S, Report # P-65775-002.Google Scholar
Fowler, T. G. and Sorgrad, E. (2000). Modelling ship transportation risk. Risk Analysis, 20, 225244.Google Scholar
Fujii, Y. and Tanaka, K. (1971). Traffic Capacity. Journal of Navigation, 24, 543552.Google Scholar
Fujii, Y., Yamanouchi, H. and Mizuki, N. (1974). Some Factors Affecting the Frequency of Accidents in Marine Traffic. II-The Probability of Stranding. III-The Effect Of Darkness on The Probability of Collision ond Stranding. Journal of Navigation, 27, 239247.Google Scholar
Dand, I. W. (2001). Approach Channel Design: The PIANC Approach. Proceedings of the International Workshop on Channel Design and Vessel Maneuverability, Norfolk, VA.Google Scholar
Goodwin, E. M. (1975). A statistical study of ship domains. Journal of Navigation, 28, 328344.CrossRefGoogle Scholar
Kaneko, F. (2002). Methods for probabilistic safety assessments of ships. Journal of Marine Science and Technology, 7, 116.Google Scholar
Kujala, P., Hanninen, M., Arola, T. and Ylitalo, J. (2009). Analysis of the Marine Traffic Safety in the Gulf of Finland. Reliablity Engineering and System Safety, 94, 13491357.CrossRefGoogle Scholar
Li, S., Meng, Q. and Qu, X. (2011). An overview of maritime waterway quantitative risk assessment models. Risk Analysis (Accepted).Google Scholar
MPA. Maritime and Port Authority of Singapore. http://www.mpa.gov.sg/sites/port_and_shipping/port/vessel_traffic_information_system(vtis)/straitrep/operational_areas.page, accessed on 30 August 2011.Google Scholar
Macduff, T. (1974). Probability of Vessel Collisions. Ocean Industry, 9, 144148.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
Mou, J. M., Tak, C. and Ligteringen, H. (2010). Study on Collision Avoidance in Busy Waterways by Using AIS Data. Ocean Engineering, 37, 483490.CrossRefGoogle Scholar
Otto, S., Pedersen, P. T., Samuelides, M. and Sames, P. C. (2002). Elements of Risk Analysis for Collision and Grounding of a RoRO Passenger ferry. Marine Structures, 15, 461474.CrossRefGoogle Scholar
Pedersen, P. (2002). Collision Risk for Fixed Offshore Structures Close to High-Density Shipping Lane. Proceedings of the Institution of Mechanical Engineers Part M: Journal of Engineering for the Maritime Environment, 216, 2944.Google Scholar
Pietrzykowski, Z. (2008). Ship's Fuzzy Domain – A Criterion for Navigational Safety in Narrow Fairways. Journal of Navigation, 61, 499514.Google Scholar
Pietrzykowski, Z. and Uriasz, J. (2009). The Ship Domain – A Criterion of Navigational Safety Assessment in an Open Sea Area. Journal of Navigation, 62, 93108.CrossRefGoogle Scholar
Qu, X., Meng, Q. and Li, S. (2011). Ship Collision Risk Assessment for the Singapore Strait. Accident Analysis and Prevention, 43, 20302036.Google Scholar
Qu, X. and Meng, Q. (2012). The economic importance of the Straits of Malacca and Singapore: an extreme-scenario analysis. Transportation Research Part E: Logistics and Transportation Review, 48, 258265.Google Scholar
@RISK. (2002). Risk Analysis and Simulation Add-in for Microsoft® Excel (version 4.5).Google Scholar
SIGTTO. (2008). Passage Planning Guide: Malacca & Singapore Straits (2nd Edition 2008). Witherby Seamanship International Ltd.Google Scholar
Szlapczynski, R. (2006). A Unified Measure of Collision Risk Derived from the Concept of a Ship Domain. Journal of Navigation, 59, 477490.Google Scholar
Tan, B. and Otay, E. N. (1999). Modelling and Analysis of Vessel Casualties Resulting from Tanker Traffic Through Narrow Waterways. Naval Research Logistics, 46, 871892.3.0.CO;2-I>CrossRefGoogle Scholar
Wang, N. (2010). An Intelligent Spatial Collision Risk Based on the Quaternion Ship Domain. Journal of Navigation, 63, 733749.Google Scholar
Wang, X. and Meng, Q. (2011). The Impact of Landbridge on the Market Shares of Asian Port. Transportation Research Part E, 47, 190203.CrossRefGoogle Scholar
Zhang, H., and Huang, S. (2006). Dynamic Control of Intention Priorities of Human-like Agents. Proceedings of the 17th European Conference on Artificial Intelligence, ECAT 2006, Italy.Google Scholar