Ship traffic through the Turkish Straits occurs in a highly constrained navigational environment, where inaccurate prepassage reports can significantly increase the risk of maritime accidents. Vessels are required to submit Sailing Plan declarations (SP-1 and SP-2) before entry, but these reports often fail to reflect the actual technical and operational condition of the ships. Commercial pressure, time constraints, and intentional misreporting can create discrepancies between declared and actual readiness, raising the likelihood of collisions, groundings, or loss of maneuverability in congested waters. This study develops a reliability-centered framework to assess accident risks associated with reporting, contributing to the literature on human reliability and uncertainty management in maritime traffic. Risk criteria were identified by reviewing regulatory requirements, accident records, and relevant literature, and refined through expert input from Vessel Traffic Services (VTS), pilotage, Port State Control (PSC), and ship operations. The framework combines the Fine–Kinney method with an Intuitionistic Fuzzy TODIM (an acronym in Portuguese for interactive and multicriteria decision-making). The results indicate that undisclosed propulsion deficiencies, steering problems, and nontransparent withdrawal from passage queues are the most critical accident precursors. These findings highlight the importance of reliable reporting and provide practical and transferable guidance for reducing the risks of maritime accidents and improving risk management for vessel traffic. In particular, the results support the prioritization of propulsion and steering system checks, as well as the closer scrutiny of vessels withdrawing from passage queues, offering actionable insights for VTS operators, PSC authorities and marine pilots.
KöseE.BaşarE.DemirciE.GüneroğluA.ErkebayŞ.Simulation of Marine Traffic in the Istanbul Strait. Simulation Modelling Practice and Theory, Vol. 11, 2003, pp. 597–608. https://doi.org/10.1016/j.simpat.2003.10.001.
3.
PlantG.Navigation Regime in the Turkish Straits for Merchant Ships in Peacetime: Safety, Environmental Protection and High Politics. Marine Policy, Vol. 20, No. 1, 1996, pp. 15–27. https://doi.org/10.1016/0308-597X(95)00009-U.
4.
Republic of Türkiye Ministry of Transport and Infrastructure. Turkish Straits Vessel Transit Statistics 2024. Directorate General of Maritime Affairs, Ankara, 2025.
5.
International Maritime Organization. Resolution A.857(20): Guidelines for Vessel Traffic Services. IMO, London, 1997.
6.
Republic of Türkiye Ministry of Transport and Infrastructure. Turkish Straits Maritime Traffic Regulations. Republic of Türkiye Ministry of Transport and Infrastructure, Ankara, 2024.
7.
Oil Companies International Marine Forum. Guidelines for Transiting the Turkish Straits, 2nd ed. OCIMF, London, 2021.
REMPEC. The Nassia Tanker Accident (1994). Regional Marine Pollution Emergency Response Centre for the Mediterranean Sea, Valletta, 2022.
10.
Republic of Türkiye Ministry of Foreign Affairs. Turkish Straits. Technical Report. Republic of Türkiye Ministry of Foreign Affairs, Ankara, 1999.
11.
OtayE. N.YenigünO.The Volgoneft-248 Oil Spill in the Marmara Sea. Technical Report. Boğaziçi University, Istanbul, 2000.
12.
Transport Safety Investigation Center. Marine Safety Investigation Report: VITASPIRIT. Ministry of Transport and Infrastructure, Ankara, 2019.
13.
CeylanB. O.AkyuzE.ArslanO.Systems-Theoretic Accident Model and Processes (STAMP) Approach to Analyse Socio-Technical Systems of Ship Allision in Narrow Waters. Ocean Engineering, Vol. 239, 2021, p. 109804. https://doi.org/10.1016/j.oceaneng.2021.109804.
14.
CeylanB. O.ElidoluG.ArslanoğluY.A Novel Approach for the Analysis of Engineering Complex System Accidents: The Casualty of the M/V Vitaspirit. Ocean Engineering, Vol. 276, 2023, p. 114217. https://doi.org/10.1016/j.oceaneng.2023.114217.
15.
ArslanO.TuranO.Analytical Investigation of Marine Casualties at the Strait of Istanbul with SWOT–AHP Method. Maritime Policy & Management, Vol. 36, No. 2, 2009, pp. 131–145. https://doi.org/10.1080/03088830902868081.
16.
KaoS.-L.LeeK.-T.ChangK.-Y.KoM.-D.A Fuzzy Logic Method for Collision Avoidance in Vessel Traffic Service. The Journal of Navigation, Vol. 60, No. 1, 2007, pp. 17–31. https://doi.org/10.1017/S0373463307003980.
ÖzbaşB.Orİ.AltıokT.Comprehensive Scenario Analysis for Mitigation of Risks of the Maritime Traffic in the Strait of Istanbul. Journal of Risk Research, Vol. 16, No. 5, 2013, pp. 541–561. https://doi.org/10.1080/13669877.2012.726239.
19.
GörçünÖ. F.BurakS. Z.Formal Safety Assessment for Ship Traffic in the Istanbul Straits. Procedia-Social and Behavioral Sciences, Vol. 207, 2015, pp. 252–261. https://doi.org/10.1016/j.sbspro.2015.10.094.
20.
UğurluÖ.ErolS.BaşarE.Life Safety and Economic Loss in Turkish Straits Accidents. Maritime Policy & Management, Vol. 43, No. 3, 2016, pp. 356–370. https://doi.org/10.1080/03088839.2014.1000992.
21.
KaraE. E. G.Risk Assessment in the Istanbul Strait Using Black Sea MOU Port State Control Inspections. Sustainability, Vol. 8, No. 4, 2016, p. 390. https://doi.org/10.3390/su8040390.
22.
EssizB.DağkıranB.Accidental Risk Analyses of the Istanbul and Çanakkale Straits. IOP Conference Series: Earth and Environmental Science, Vol. 95, 2017, p. 042042. https://doi.org/10.1088/1755-1315/95/4/042042.
23.
KamalB.ÇakırE.Data-Driven Bayes Approach to Marine Accidents in the Istanbul Strait. Applied Ocean Research, Vol. 123, 2022, p. 103180. https://doi.org/10.1016/j.apor.2022.103180.
24.
EkiciC. V.ArslanO.OzturkU.Fuzzy C-Means Clustering of Ships Passing Through Turkish Straits. In Intelligent and Fuzzy Systems (INFUS 2022) (KahramanC.TolgaA. C.Cevik OnarS.CebiS.OztaysiB.SariI. U., eds.), Springer, Cham, 2022, pp. 354–361. https://doi.org/10.1007/978-3-031-09173-5_43.
25.
TonoğluF.AtalarF.Başkanİ. B.YildizS.UğurluÖ.WangJ.A New Hybrid Approach for Determining Sector-Specific Risk Factors in Turkish Straits: Fuzzy AHP-PRAT Technique. Ocean Engineering, Vol. 253, 2022, p. 111280. https://doi.org/10.1016/j.oceaneng.2022.111280.
26.
YildizS.UğurluÖ.LoughneyS.WangJ.TonoğluF.Spatial and Statistical Analysis of Operational Conditions Influencing Accident Formation in Narrow Waterways: A Case Study of Istanbul Strait and Dover Strait. Ocean Engineering, Vol. 266, 2022, p. 112647. https://doi.org/10.1016/j.oceaneng.2022.112647.
27.
OrhanM.GümüşF.ArslanÖ.Risk Assessment of the Turkish Straits for Service Providers Using Fuzzy Cognitive Maps. Proc. The 29th International Maritime Lecturers Association (IMLA) Conference, Istanbul, 2024.
28.
EkiciC. V.ÖztürkÜ.ŞenolY. E.A Data-Driven Ship Risk Profile Model for Turkish Straits (TS-SRP) Using Machine Learning. Ocean Engineering, Vol. 311, 2024, p. 119002. https://doi.org/10.1016/j.oceaneng.2024.119002.
29.
WangQ.GuanH.LiL.LiK.ShaZ.ChenQ.Collision Avoidance Method for Intelligent Ships in Inland Complex Waterways Based on MVO–QSD Models. Regional Studies in Marine Science, Vol. 71, 2025, p. 104312. https://doi.org/10.1016/j.rsma.2025.104312.
30.
FengK.LiJ.ChenT.WangX.WangJ.ChenL.WangQ.ShenC.LiY.JiangY.Complexity Analysis of Navigation Situation of Intelligent Ships in Port Area with Multi-Factor Coupling. Regional Studies in Marine Science, Vol. 72, 2025, p. 104503. https://doi.org/10.1016/j.rsma.2025.104503.
31.
JiacaiP. A. N.MengjieL. U.FengM. A.Review of Ship Navigational Safety in the Arctic Northwest Passage. Regional Studies in Marine Science, Vol. 71, 2025, p. 104229. https://doi.org/10.1016/j.rsma.2025.104229.
32.
JinL.LiP.WangY.YangZ.Risk Analysis of Arctic Navigation Using Text Mining (TM) and Improved Association Rule Mining (ARM) Methods. Regional Studies in Marine Science, Vol. 69, 2024, p. 103990. https://doi.org/10.1016/j.rsma.2024.103990.
SezerŞ. İ.CeylanB. O.AkyüzE.GardoniP.Improved Z-Number and Fault Tree Analysis to Predict the Risk of Air Pollution due to Ship Boiler Operation. Marine Pollution Bulletin, Vol. 206, 2024, p. 116801. https://doi.org/10.1016/j.marpolbul.2024.116801.
35.
CeylanB. O.SezerŞ. İ.AkyuzE.An Integrated System Theoretic Accident Model and Process (STAMP)–Bayesian Network (BN) for Safety Analysis of Water Mist System on Tanker Ships. Applied Ocean Research, Vol. 154, 2025, p. 104344. https://doi.org/10.1016/j.apor.2024.104344.
36.
PedrielliG.XingY.PehJ. H.KohK. W.NgS. H.A Real Time Simulation Optimization Framework for Vessel Collision Avoidance and the Case of Singapore Strait. IEEE Transactions on Intelligent Transportation Systems, Vol. 21, No. 3, 2020, pp. 1204–1215. https://doi.org/10.1109/TITS.2019.2903824.
37.
KangL.LuZ.MengQ.GaoS.WangF.Maritime Simulator Based Determination of Minimum DCPA and TCPA in Head-On Ship-To-Ship Collision Avoidance in Confined Waters. Transportmetrica A: Transport Science, Vol. 15, No. 2, 2019, pp. 1124–1144. https://doi.org/10.1080/23249935.2019.1567617.
ZhangL.MengQ.Probabilistic Ship Domain with Applications to Ship Collision Risk Assessment. Ocean Engineering, Vol. 186, 2019, p. 106130. https://doi.org/10.1016/j.oceaneng.2019.106130.
40.
LoughneyS.YildizS.UğurluÖ.KontovasC.WangJ.Dynamic Risk Modelling of Maritime Accidents Based on HFACS-PV and Bayesian Networks. Ocean Engineering, Vol. 355, 2026, p. 125099. https://doi.org/10.1016/j.oceaneng.2026.125099.
41.
SotiralisP.VentikosN. P.HamannR.GolyshevP.TeixeiraA. P.Incorporation of Human Factors into Ship Collision Risk Models Focusing on Human-Centred Design Aspects. Reliability Engineering & System Safety, Vol. 156, 2016, pp. 210–227. https://doi.org/10.1016/j.ress.2016.08.007.
42.
KhanI. A.RahmanS.Review and Analysis of Blockage of Suez Canal Region due to Giant Container Ship. Marine Technology Society Journal, Vol. 55, No. 5, 2021, pp. 39–43. https://doi.org/10.4031/MTSJ.55.5.5.
43.
OqdaK.IbrahimK. M.MustafaA. I.AllamR. G.SaadM. A.AslA. I.SamieM. A. S. A., et al. Smart ROUV Advances for Enhanced Navigation in the Suez Canal. Scientific Reports, Vol. 15, 2025, p. 39011. https://doi.org/10.1038/s41598-025-23281-8.
44.
YangJ.XieW.XieH.SunY.WangX.Navigational Risk Evaluation of One-Way Channels: Modeling and Application to the Suez Canal. Journal of Marine Science and Engineering, Vol. 13, No. 10, 2025, p. 1864. https://doi.org/10.3390/jmse13101864.
45.
FuentesG.AdlandR.A Spatial Framework for Extracting Suez Canal Transit Information from AIS. Proc. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, IEEE, New York, 2020, pp. 586–590. https://doi.org/10.1109/IEEM45057.2020.9309882.
46.
Harun-Al-RashidA.YangC.-S.ShinD.-W.Detection of Maritime Traffic Anomalies Using Satellite-AIS and Multisensory Satellite Imageries: Application to the 2021 Suez Canal Obstruction. The Journal of Navigation, Vol. 75, No. 5, 2022, pp. 1082–1099. https://doi.org/10.1017/S0373463322000364.
47.
KinneyR. L.WiruthK. Practical Risk Analysis for Safety Management. NWC-TP-5865. Naval Weapon Center, China Lake, CA, 1976.
48.
FineW. T.Mathematical Evaluation for Controlling Hazards. Naval Ordnance Laboratory, White Oak, MD, 1971.
49.
KokangülA.PolatU.DağsuyuC.A New Approximation for Risk Assessment Using the AHP and Fine Kinney Methodologies. Safety Science, Vol. 91, 2017, pp. 24–32. https://doi.org/10.1016/j.ssci.2016.07.015.
50.
PajićV.AndrejićM.Risk Analysis in Internal Transport: An Evaluation of Occupational Health and Safety Using the Fine-Kinney Method. Journal of Operational and Strategic Analytics, Vol. 1, No. 4, 2023, pp. 147–159. https://doi.org/10.56578/josa010401.
ChungH.-Y.TingT.-H.ChangK.-H.An Intuitionistic Fuzzy Set-Based Risk Priority Number Method for Chemical Experiment Risk Evaluation. Systems, Vol. 12, No. 5, 2024, p. 155. https://doi.org/10.3390/systems12050155.
53.
WuY.WuC.ZhouJ.ZhangB.XuC.YanY.LiuF.A DEMATEL-TODIM Based Decision Framework for PV Power Generation Project in Expressway Service Area Under an Intuitionistic Fuzzy Environment. Journal of Cleaner Production, Vol. 247, 2020, p. 119099. https://doi.org/10.1016/j.jclepro.2019.119099.
54.
ElidoluG.UflazE.AydinM.CelikE.AkyuzE.ArslanO.Numerical Risk Analysis of Gas Freeing Processes on Oil/Chemical Tankers. Ocean Engineering, Vol. 266, 2022, p. 113082. https://doi.org/10.1016/j.oceaneng.2022.113082.
55.
SongW.MingX.WuZ.An Integrated Framework for Service Concept Evaluation Based on Rough Sets and Grey-TODIM Method. Soft Computing, Vol. 19, 2015, pp. 243–261.
56.
GulM.MeteS.SerinF.CelikE. (eds). Fine–Kinney-Based Fuzzy Multi-Criteria Occupational Risk Assessment. In Occupational Risk Assessment: Approaches, Case Studies and Python Applications. Springer, Cham, 2021, pp. 82–102.
57.
GomesL. F. A. M.LimaM. M. P. P.TODIM: Basics and Application to Multicriteria Ranking of Projects with Environmental Impacts. Foundations of Computing and Decision Sciences, Vol. 16, No. 4, 1992, pp. 113–127.
58.
AshoftehP.-S.PouraliM.Ranking the Optimal Combination of Low-Impact Urban Development Systems Under Climate Change with the TODIM Multi-Criteria Decision-Making Method. Journal of Cleaner Production, Vol. 434, 2024, p. 140108. https://doi.org/10.1016/j.jclepro.2023.140108.
59.
HuJ.YangY.ChenX.A TODIM-Based Three-Way Decision Model for Medical Treatment Selection. International Journal of Fuzzy Systems, Vol. 20, No. 4, 2018, pp. 1240–1255. https://doi.org/10.1007/s40815-017-0320-3.
60.
TangJ.LiuX.WangW.Consensus-Based Generalized TODIM Approach for Occupational Health and Safety Risk Analysis with Opinion Interactions. Applied Soft Computing, Vol. 150, 2024, p. 111093. https://doi.org/10.1016/j.asoc.2023.111093.
