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Volume 16 - Summer and Fall 2021                   ijmt 2021, 16 - Summer and Fall 2021: 53-61 | Back to browse issues page

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Allahmoradi Q, Panahi R, Edraki R, Akbari H. Maritime Traffic Complexity Visualization: A New Method for Identification of High Opportunity and High Risk Areas. ijmt 2021; 16 :53-61
URL: http://ijmt.ir/article-1-739-en.html
1- Tarbiat Modares University
2- University of Manitoba
Abstract:   (2300 Views)
A clear understanding of marine traffic complexity is vital for safe and efficient navigation inside ports (e.g., pilotage inside the basin). Built on statistical analysis of vessels’ speed and course over ground extracted from satellite-based Automatic Identification System (AIS) data, an index of maritime traffic situation is developed in this research. After zoning the port basin, this index is calculated at each zone based on a combination of statistical measures (e.g., mean and standard deviation of speed and course over ground), in which vessels’ class based on their size and targeted pier is also incorporated. The model could effectively increase the situational awareness by simple monitoring of navigation activities and reflecting improvements. This becomes possible by identification of high opportunity and high risk zones, i.e., those with high index value which call for operation modification which are far from and close to the infrastructures (e.g., breakwaters), respectively. To explore the model outcome, it is typically applied on the Rajaee port - the largest port of Iran located in the Persian Gulf - and output are discussed with port’s maritime operators to analyze results. This resulted in identification of challenging zones for which pilotage plans could be improved. Also, it provided insight for better implementation of the basin which also could be considered in future development plans of the port.
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Type of Study: Research Paper | Subject: Maritime Transport and Port Management
Received: 2021/11/26 | Accepted: 2022/04/9

References
1. Kristiansen, S., (2013), Maritime transportation: safety management and risk analysis. 1st ed. Oxford: Butterworth-Heinemann, p.6. [DOI:10.4324/978080473369]
2. Zhang, D., Yan, X. P., Yang, Z. L., Wall, A., & Wang, J. (2013). Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River, Reliability Engineering & System Safety, 118, 93-105. [DOI:10.1016/j.ress.2013.04.006]
3. IMO (2002) Guidelines for Formal Safety Assessment (FSA) for use in the IMO rule-making process. MSC/Circ. 1023. London IMO (2012) Formal Safety Assessment, Outcome of MSC 90. Draft revised FSA guidelines and darft HEAP guidelines.
4. Fujii, Y. and Shiobara, R., (1971), The analysis of traffic accidents, The Journal of Navigation, Vol.24(4) p.534-543. [DOI:10.1017/S0373463300022372]
5. Macduff, T., (1974), The probability of vessel collisions, Ocean Industry, 9(9): 144-148.
6. Jiacai, P., Jiang, Q., Jinxing, H. and Zheping, S., (2012), An AIS data visualization model for assessing maritime traffic situation and its applications, Procedia Engineering, Vol.29, p.365-369. [DOI:10.1016/j.proeng.2011.12.724]
7. Mazaheri, A., Montewka, J. and Kujala, P., (2014), Modeling the risk of ship grounding-a literature review from a risk management perspective, WMU journal of maritime affairs, Vol.13(2), p.269-297. [DOI:10.1007/s13437-013-0056-3]
8. Olindersson, F. and Janson, C.E, (2015), Development of a software to identify and analyse marine traffic situations, International Conference on Marine Simulation and Ship Manoeuvrability (MARSIM), Newcastle, United Kingdom. [DOI:10.12716/1001.09.01.14]
9. Zaman, M.B., Kobayashi, E., Wakabayashi, N. and Maimun, A., (2015), Risk of navigation for marine traffic in the Malacca Strait using AIS, Procedia Earth and Planetary Science, Vol.14, p.33-40. [DOI:10.1016/j.proeps.2015.07.082]
10. Williams, G., (1997), Chaos theory tamed. 1st ed. London: CRC Press, p.15. [DOI:10.1201/9781482295412]
11. Goulielmos, A.M., (2004), A treatise of randomness tested also in marine accidents. Disaster Prevention and Management, An International Journal, Vol.13(3), p. 208-217. [DOI:10.1108/09653560410541803]
12. Mazaheri, A., (2017), A framework for evidence-based risk modeling of ship grounding, PhD Thesis, Aalto university, Finland.
13. 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, Vol.62, p.427-440. [DOI:10.1016/j.ssci.2013.10.002]
14. Hanninen, M. and Kujala, P., (2009), The effects of causation probability on the ship collision statistics in the Gulf of Finland, Marine Navigation and Safety of Sea Transportation, London: Taylor and Francis, p.267-272.
15. Cazzanti, L. and Pallotta, G., (2015), Mining maritime vessel traffic: Promises, challenges, techniques In OCEANS-Genova, Italy. [DOI:10.1109/OCEANS-Genova.2015.7271555]
16. Altman, D.G., Machin, D., Bryant T.N., Gardner, M.J., (2001) Statistics with confidence. 2nd ed. London: BMJ Books, p.28-31.

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