Hostname: page-component-848d4c4894-wg55d Total loading time: 0 Render date: 2024-05-18T23:55:12.346Z Has data issue: false hasContentIssue false
  • English
  • Français

A method for estimating the number of collision candidates in two waterways – for all intersection angles

Published online by Cambridge University Press:  21 February 2022

Fujio Kaneko Open the ORCID record for Fujio Kaneko [Opens in a new window]
Fujio Kaneko*
Affiliation:
Department of Marine Risk Assessment, National Maritime Research Institute (NMRI), National Institute of Maritime and Aviation Technology, Mitaka, Tokyo, Japan
*
E-mail: kaneko@m.mpat.go.jp
Get access Rights & Permissions [Opens in a new window]

Abstract

Estimating the collision frequency of ships (F) is important for assessing collision risk on waterways. To date, F has been estimated as the product of the number of collision candidates $({N_{a }})$ and the causation probability $({P_c})$: $F = {N_{a}} \cdot {P_c}$, where ${N_{a }}$ represents the number of collisions that occur when related ships continue on course with no intervention, and ${P_c}$ is the probability that collision avoidance fails. Fujii developed a general method and Pedersen formulated it to estimate ${N_{a }}$ in an intersectional area. Their method is generally called ‘the geometric method’ because collision candidates are estimated only from the geometric relationship between two ships. The method has been used in many projects to estimate F in waterways; however, its use should be limited to intersection angles ranging from 10° to 170°. This paper presents a method, statistically verified by computer simulation, that can be used at all intersection angles to overcome this limitation. Moreover, it demonstrates strong agreement with Pedersen's method at intersection angles of 10° to 170°.

Keywords

collision candidateriskintersection angle
Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 2 , March 2022 , pp. 400 - 420
Check for updates
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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

Čorić, M., Mandžuka, S., Gudelj, A. and Lušić, Z. (2021). Quantitative ship collision frequency estimation models: A review. Journal of Marine Science and Engineering, 9, 533. Available at: https://www.mdpi.com/2077-1312/9/5/533.CrossRefGoogle Scholar
COWI. (2008). Risk Analysis of Sea Traffic in the Area around Bornholm. COWI for Søfartsstyrelsen (online). Available at: https://www.yumpu.com/en/document/read/35601367/risk-analysis-of-sea-traffic-in-the-area-around-bornholm-2008-vtt. Accessed 1 March 2021.Google Scholar
Friis-Hansen, P. (2008). Basic Modelling Principles for Prediction of Collision and Grounding Frequencies, Working document of the IALA Waterway Risk Assessment Programme MK II, Rev. 4. Available at: https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.iala-aism.org%2Fwiki%2Fiwrap%2Fimages%2F2%2F2b%2FIWRAP_Theory.pdf&data=04%7C01%7Ckavitha%40novatechset.com%7Cfedc6a7d9678476664c608d9ed0b4c8e%7Ca03a7f6cfbc84b5fb16bf634dbe1a862%7C1%7C0%7C637801455848495026%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=ruRe2ja8Ihp80Z72TL5SVLaRKwaBaW4JwomQm%2BHj77I%3D&reserved=0.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 stranding. The Journal of Navigation, 27, 239–252.CrossRefGoogle Scholar
Kaneko, F. (2002). Methods for probabilistic safety assessments of ships. Journal of Marine Science and Technology, 7(1), 1–16.CrossRefGoogle Scholar
Kaneko, F. (2013). An Improvement on a Method for Estimating Number of Collision Candidates Between Ships. Proceedings of the 6th ICCGS (Collision and Grounding of Ships and Offshore Structures), Trondheim, Norway.CrossRefGoogle Scholar
Kujala, P., Hanninen, M., Arola, T. and Ylitalo, J. (2009). Analysis of the marine traffic safety in the Gulf of Finland. Reliability Engineering and System Safety, 94(8), 1349–1357.CrossRefGoogle Scholar
Lušić, Z. and Čorić, M. (2015). Models for estimating the potential number of ship collisions. The Journal of Navigation, 68, 735–749.CrossRefGoogle Scholar
Montewka, J., Hinz, T., Kujala, P. and Matusiak, J. (2010). Probability modelling of vessel collisions. Reliability Engineering and System Safety, 95(5), 573–589.CrossRefGoogle Scholar
Pedersen, P. T. (1995). Collision and Grounding Mechanics. Proceedings of WEMT 95, Copenhagen: The Danish Society of Naval Architecture and Marine Engineering, 125–157.Google Scholar
Pedersen, P. T. (2010). Review and application of ship collision and grounding analysis procedures. Marine Structures, 23, 241–262.CrossRefGoogle Scholar
Silveira, P., Teixeira, A. P. and Soares, C. G. (2014). Assessment of Ship Collision Estimation Methods Using AIS Data. Proceedings of 2nd International Conference on Maritime Technology and Engineering (MARTECH 2014), Lisbon, Portugal.Google Scholar
Suyi, L., Qiang, M. and Xiaobo, Q. (2012). An overview of maritime waterway quantitative risk assessment models. Risk Analysis, 32(3), 496–512.Google Scholar
Ylitalo, J. (2009). Ship-Ship Collision Probability of the Crossing Area between Helsinki and Tallinn. Mat-2⋅4108 Independent research projects in applied mathematics, Helsinki University of Technology, Finland. http://salserver.org.aalto.fi/vanhat_sivut/Opinnot/Mat-2.4108/pdf-files/eyli09.pdf. Accessed 1 March 2021.Google Scholar