Annotation:
The work is devoted to the development of algorithms for a predictive and analytical system for studying the consequences of transport accidents on inland water transport.
For these purposes, the authors have analyzed international and Russian sources grouped as follows: studies on hazard identification and estimation of probability (or frequency) of traffic accidents, evaluation of consequences of such accidents, and the development of intellectual decision support systems. The analysis of methods applied within each of the groups has enabled the formulation of requirements for the developed forecast and analytical system: orientation to the traffic accident database under development, required modules of the forecast and analytical system available, consideration of geometrical models of waterways, and combination of approaches to developed algorithms. During the studies, the following methods were used: analysis of the Russian and international literature, logical and mathematical description, generalization, and decomposition backed up by theoretical premises of statistical methods of data processing. Considering the tasks set, the following modules of the forecast and analytical system are defined: information entry and correction, traffic accident risk identification, determining consequences of traffic accidents, modelling a spread of contamination caused by a specific traffic accident. For each structural module of the forecast and analytical system, input and output data are specified. Based on the approaches to the structure of the forecast and analytical system, the algorithms of the overall operation of the system and of each module have been developed. For further research, the development in accordance with proposed algorithms of specific software for approbation purposes is planned.
References:
1. Домнина О.Л., Пластинин А.Е. Управление в чрезвычайных ситуациях на внутреннем водном транспорте // Безопасность труда в промышленности. 2025. № 1. С. 59–66. DOI: 10.24000/0409-2961-2025-1-59-66
Domnina O.L., Plastinin A.E. Emergency Management in Inland Waterway Transport. Bezopasnost Truda v Promyshlennosti = Occupational Safety in Industry. 2025. № 1. pp. 59–66. (In Russ.). DOI: 10.24000/0409-2961-2025-1-59-66
2. Домнина О.Л. Оценка риска экологических последствий от транспортных происшествий с сухогрузными судами на примере Волжского бассейна // Морские интеллектуальные технологии. 2022. Т. 1. № 1. С. 187–193. DOI: DOI: 10.37220/MIT.2022.55.1.025
Domnina O.L. Risk Assessment of Environmental Consequences from Transport Accidents with Dry Cargo Vessels on the Example of the Volga Basin. Morskie intellektualnye tekhnologii = Marine intellectual technologies. 2022. Vol. 1. № 1. рр. 187–193. (In Russ.). DOI: 10.37220/MIT.2022.55.1.025
3. Wang L., Huang R., Jin M., Zhang C. Domino effect in marine accidents: Evidence from temporal association rules. Transport Policy. 2021. Vol. 103. pp. 236–244. DOI: 10.1016/j.tranpol.2021.02.006
4. Оценка риска возникновения транспортных происшествий на реках в границах республики Татарстан / О.Л. Домнина, А.Е. Пластинин, Е.А. Батанина, В.С. Наумов // Морские интеллектуальные технологии. 2019. № 4-2 (46). С. 79–84.
Domnina O.L., Plastinin A.E., Batanina E.A., Naumov V.S. Risk assessment of transport accidents on rivers in the borders of the republic of Tatarstan. Morskie intellektualnye tekhnologii = Marine intellectual technologies. 2019. № 4-2 (46). pp. 79–84. (In Russ.).
5. Наумов В.С., Нестерова О.С. Оценка вероятности загрязнения экологически чувствительных зон внутренних водных путей нефтью и нефтепродуктами // Вестник государственного университета морского и речного флота им. адмирала С.О. Макарова. 2015. № 4 (32). С. 66–73.
Naumov V.S., Nesterova O.S. Asessment of the probability of pollution of environmentally sensitive areas internal waterways oil and oil products. Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova = Bulletin of the State University of the Sea and River Fleet named after Admiral S.O. Makarov. 2015. № 4 (32). pp. 66–73. (In Russ.).
6. Du L., Goerlandt F., Kujala P. Review and analysis of methods for assessing maritime waterway risk based on non-accident critical events detected from AIS data. Reliability Engineering and System Safety. 2020. Vol. 200. DOI: 10.1016/j.ress.2020.106933
7. Zhang M., Taimuri G., Zhang J., Zhang D., Yan X., Kujala P., Hirdarais S. Systems driven intelligent decision support methods for ship collision and grounding prevention: Present status, possible solutions, and challenges. Reliability Engineering and System Safety. 2025. Vol. 253. DOI: 10.1016/j.ress.2024.110489
8. Huang Y., Chen L., Chen P., Negenborn R.R., Van Gelder P.H.A.J.M. Ship collision avoidance methods: State-of-the-art. Safety Science. 2020. Vol. 121. pp. 451–473. DOI: 10.1016/j.ssci.2019.09.018
9. Chen P., Huang Y., Mou J., Van Gelder P.H.A.J.M. Probabilistic risk analysis for ship-ship collision: State-of-the-art. Safety Science. 2019. Vol. 117. pp. 108–122. DOI: 10.1016/j.ssci.2019.04.014
10. Deeb H., Mehdi R.A., Hahn A. A review of damage assessment models in the maritime domain. Ships and Offshore Structures. 2017. Vol. 12. Iss. sup1. pp. S31–S54. DOI: 10.1080/17445302.2016.1278317
11. Galić S., Lušić Z., Mladenović S., Gudelj A. A Chronological overview of scientific research on ship grounding frequency estimation models. Journal of Marine Science and Engineering. 2022 Vol. 10. Iss. 2. DOI: 10.3390/jmse10020207
12. Aydin M., Akyuz E., Turan O., Arslan O. Validation of risk analysis for ship collision in narrow waters by using fuzzy Bayesian networks approach. Ocean Engineering. 2021. Vol. 231. DOI: 10.1016/j.oceaneng.2021.108973
13. Ozlem S., Altan Y.C., Otay E.N., Or İ. Grounding probability in narrow waterways. The Journal of Navigation. Vol. 73. Iss. 2. pp. 267–281. DOI: 10.1017/S0373463319000572
14. Ung S.T. Evaluation of human error contribution to oil tanker collision using fault tree analysis and modified fuzzy Bayesian Network based CREAM. Ocean Engineering. 2019. Vol. 179. pp. 159–172. DOI: 10.1016/j.oceaneng.2019.03.031
15. Sakar C., Toz A.C., Buber M., Koseoglu B. Risk analysis of grounding accidents by mapping a fault tree into a Bayesian network. Applied Ocean Research. 2021. Vol. 113. DOI: 10.1016/j.apor.2021.102764
16. Актуализация руководств по безопасности в области оценки риска аварий на производственных объектах / М.В. Лисанов, А.А. Агапов, С.Х. Зайнетдинов и др. // Безопасность труда в промышленности. 2023. № 7. С. 85–92. DOI: 10.24000/0409-2961-2023-7-85-92
Lisanov M.V., Agapov A.A., Zaynetdinov S.Kh., Sumskoy S.I., Sofyin A.S. Updating Safety Guides in the Field of Accident Risk Assessment at the Production Facilities. Bezopasnost Truda v Promyshlennosti = Occupational Safety in Industry. 2023. № 7. pp. 85–92. (In Russ.). DOI: 10.24000/0409-2961-2023-7-85-92
17. Xue J., Van Gelder P.H.A.J.M., Reniers G., Papadimitriou E., Wu C. Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships’ maneuvering decisions using grey and fuzzy theories. Safety Science. 2019. Vol. 120. pp. 323–340. DOI: 10.1016/j.ssci.2019.07.019
18. Hörteborn A., Ringsberg J.W. A method for risk analysis of ship collisions with stationary infrastructure using AIS data and a ship manoeuvring simulator. Ocean Engineering. 2021. Vol. 235. DOI: 10.1016/j.oceaneng.2021.109396
19. Kujala P., Hänninen M., Arola T., Ylitalo J. Analysis of the marine traffic safety in the Gulf of Finland. Reliability Engineering and System Safety. 2009. Vol. 94. Iss. 8. pp. 1349–1357. DOI: 10.1016/j.ress.2009.02.028
20. Домнина О.Л., Липатов И.В. Моделирование процессов распространения загрязнения при аварии сухогрузных судов // Научные проблемы водного транспорта. 2022. № 71 (2). С. 239–252. DOI: 10.37890/jwt.vi71.267
Domnina O.L., Lipatov I.V. Modeling of pollution expansion processes in case of dry cargo ship accidents. Nauchnye problemy vodnogo transporta = Russian Journal of Water Transport. 2022. № 71 (2). pp. 239–252. (In Russ.). DOI: 10.37890/jwt.vi71.267
21. Kummer Y., Youhanan L., Hirsch P. Operational analysis and optimization of a water-based municipal solid waste management system with hybrid simulation modeling. Sustainable Cities and Society. 2023. Vol. 99. DOI: 10.1016/j.scs.2023.104890
22. Борщев А.В. Практическое агентное моделирование и его место в арсенале аналитика. URL: https://www.anylogic.ru/upload/iblock/e22/e22698cc27c31a100da5ba47ff2ade54.pdf (дата обращения: 01.03.2025).
Borshchev A.V. Practical agent-based modeling and its place among analyst tools. Available at: https://www.anylogic.ru/upload/iblock/e22/e22698cc27c31a100da5ba47ff2ade54.pdf (accessed: March 1, 2025). (In Russ.).
23. Казанцев А.Ю. Применение искусственного интеллекта в предотвращении и минимизации сбросов нефтесодержащих вод с судов // Каспийский научный журнал. 2024. № 1. С. 9–20.
Kazantsev A.Yu. Application of artificial intelligence in preventing and minimizing discharges of oily water from ships. Kaspijskij nauchnyj zhurnal = Caspian Scientific Journal. 2024. № 1. рр. 9–20. (In Russ.).
Domnina O.L., Plastinin A.E. Emergency Management in Inland Waterway Transport. Bezopasnost Truda v Promyshlennosti = Occupational Safety in Industry. 2025. № 1. pp. 59–66. (In Russ.). DOI: 10.24000/0409-2961-2025-1-59-66
2. Домнина О.Л. Оценка риска экологических последствий от транспортных происшествий с сухогрузными судами на примере Волжского бассейна // Морские интеллектуальные технологии. 2022. Т. 1. № 1. С. 187–193. DOI: DOI: 10.37220/MIT.2022.55.1.025
Domnina O.L. Risk Assessment of Environmental Consequences from Transport Accidents with Dry Cargo Vessels on the Example of the Volga Basin. Morskie intellektualnye tekhnologii = Marine intellectual technologies. 2022. Vol. 1. № 1. рр. 187–193. (In Russ.). DOI: 10.37220/MIT.2022.55.1.025
3. Wang L., Huang R., Jin M., Zhang C. Domino effect in marine accidents: Evidence from temporal association rules. Transport Policy. 2021. Vol. 103. pp. 236–244. DOI: 10.1016/j.tranpol.2021.02.006
4. Оценка риска возникновения транспортных происшествий на реках в границах республики Татарстан / О.Л. Домнина, А.Е. Пластинин, Е.А. Батанина, В.С. Наумов // Морские интеллектуальные технологии. 2019. № 4-2 (46). С. 79–84.
Domnina O.L., Plastinin A.E., Batanina E.A., Naumov V.S. Risk assessment of transport accidents on rivers in the borders of the republic of Tatarstan. Morskie intellektualnye tekhnologii = Marine intellectual technologies. 2019. № 4-2 (46). pp. 79–84. (In Russ.).
5. Наумов В.С., Нестерова О.С. Оценка вероятности загрязнения экологически чувствительных зон внутренних водных путей нефтью и нефтепродуктами // Вестник государственного университета морского и речного флота им. адмирала С.О. Макарова. 2015. № 4 (32). С. 66–73.
Naumov V.S., Nesterova O.S. Asessment of the probability of pollution of environmentally sensitive areas internal waterways oil and oil products. Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova = Bulletin of the State University of the Sea and River Fleet named after Admiral S.O. Makarov. 2015. № 4 (32). pp. 66–73. (In Russ.).
6. Du L., Goerlandt F., Kujala P. Review and analysis of methods for assessing maritime waterway risk based on non-accident critical events detected from AIS data. Reliability Engineering and System Safety. 2020. Vol. 200. DOI: 10.1016/j.ress.2020.106933
7. Zhang M., Taimuri G., Zhang J., Zhang D., Yan X., Kujala P., Hirdarais S. Systems driven intelligent decision support methods for ship collision and grounding prevention: Present status, possible solutions, and challenges. Reliability Engineering and System Safety. 2025. Vol. 253. DOI: 10.1016/j.ress.2024.110489
8. Huang Y., Chen L., Chen P., Negenborn R.R., Van Gelder P.H.A.J.M. Ship collision avoidance methods: State-of-the-art. Safety Science. 2020. Vol. 121. pp. 451–473. DOI: 10.1016/j.ssci.2019.09.018
9. Chen P., Huang Y., Mou J., Van Gelder P.H.A.J.M. Probabilistic risk analysis for ship-ship collision: State-of-the-art. Safety Science. 2019. Vol. 117. pp. 108–122. DOI: 10.1016/j.ssci.2019.04.014
10. Deeb H., Mehdi R.A., Hahn A. A review of damage assessment models in the maritime domain. Ships and Offshore Structures. 2017. Vol. 12. Iss. sup1. pp. S31–S54. DOI: 10.1080/17445302.2016.1278317
11. Galić S., Lušić Z., Mladenović S., Gudelj A. A Chronological overview of scientific research on ship grounding frequency estimation models. Journal of Marine Science and Engineering. 2022 Vol. 10. Iss. 2. DOI: 10.3390/jmse10020207
12. Aydin M., Akyuz E., Turan O., Arslan O. Validation of risk analysis for ship collision in narrow waters by using fuzzy Bayesian networks approach. Ocean Engineering. 2021. Vol. 231. DOI: 10.1016/j.oceaneng.2021.108973
13. Ozlem S., Altan Y.C., Otay E.N., Or İ. Grounding probability in narrow waterways. The Journal of Navigation. Vol. 73. Iss. 2. pp. 267–281. DOI: 10.1017/S0373463319000572
14. Ung S.T. Evaluation of human error contribution to oil tanker collision using fault tree analysis and modified fuzzy Bayesian Network based CREAM. Ocean Engineering. 2019. Vol. 179. pp. 159–172. DOI: 10.1016/j.oceaneng.2019.03.031
15. Sakar C., Toz A.C., Buber M., Koseoglu B. Risk analysis of grounding accidents by mapping a fault tree into a Bayesian network. Applied Ocean Research. 2021. Vol. 113. DOI: 10.1016/j.apor.2021.102764
16. Актуализация руководств по безопасности в области оценки риска аварий на производственных объектах / М.В. Лисанов, А.А. Агапов, С.Х. Зайнетдинов и др. // Безопасность труда в промышленности. 2023. № 7. С. 85–92. DOI: 10.24000/0409-2961-2023-7-85-92
Lisanov M.V., Agapov A.A., Zaynetdinov S.Kh., Sumskoy S.I., Sofyin A.S. Updating Safety Guides in the Field of Accident Risk Assessment at the Production Facilities. Bezopasnost Truda v Promyshlennosti = Occupational Safety in Industry. 2023. № 7. pp. 85–92. (In Russ.). DOI: 10.24000/0409-2961-2023-7-85-92
17. Xue J., Van Gelder P.H.A.J.M., Reniers G., Papadimitriou E., Wu C. Multi-attribute decision-making method for prioritizing maritime traffic safety influencing factors of autonomous ships’ maneuvering decisions using grey and fuzzy theories. Safety Science. 2019. Vol. 120. pp. 323–340. DOI: 10.1016/j.ssci.2019.07.019
18. Hörteborn A., Ringsberg J.W. A method for risk analysis of ship collisions with stationary infrastructure using AIS data and a ship manoeuvring simulator. Ocean Engineering. 2021. Vol. 235. DOI: 10.1016/j.oceaneng.2021.109396
19. Kujala P., Hänninen M., Arola T., Ylitalo J. Analysis of the marine traffic safety in the Gulf of Finland. Reliability Engineering and System Safety. 2009. Vol. 94. Iss. 8. pp. 1349–1357. DOI: 10.1016/j.ress.2009.02.028
20. Домнина О.Л., Липатов И.В. Моделирование процессов распространения загрязнения при аварии сухогрузных судов // Научные проблемы водного транспорта. 2022. № 71 (2). С. 239–252. DOI: 10.37890/jwt.vi71.267
Domnina O.L., Lipatov I.V. Modeling of pollution expansion processes in case of dry cargo ship accidents. Nauchnye problemy vodnogo transporta = Russian Journal of Water Transport. 2022. № 71 (2). pp. 239–252. (In Russ.). DOI: 10.37890/jwt.vi71.267
21. Kummer Y., Youhanan L., Hirsch P. Operational analysis and optimization of a water-based municipal solid waste management system with hybrid simulation modeling. Sustainable Cities and Society. 2023. Vol. 99. DOI: 10.1016/j.scs.2023.104890
22. Борщев А.В. Практическое агентное моделирование и его место в арсенале аналитика. URL: https://www.anylogic.ru/upload/iblock/e22/e22698cc27c31a100da5ba47ff2ade54.pdf (дата обращения: 01.03.2025).
Borshchev A.V. Practical agent-based modeling and its place among analyst tools. Available at: https://www.anylogic.ru/upload/iblock/e22/e22698cc27c31a100da5ba47ff2ade54.pdf (accessed: March 1, 2025). (In Russ.).
23. Казанцев А.Ю. Применение искусственного интеллекта в предотвращении и минимизации сбросов нефтесодержащих вод с судов // Каспийский научный журнал. 2024. № 1. С. 9–20.
Kazantsev A.Yu. Application of artificial intelligence in preventing and minimizing discharges of oily water from ships. Kaspijskij nauchnyj zhurnal = Caspian Scientific Journal. 2024. № 1. рр. 9–20. (In Russ.).