Vessels route planning under ice conditions

This paper is devoted to the problem of navigation safety in ice-covered sea areas. The route planning is examined as a means of lessening the impact of ice upon a vessel as it follows its course, taking into consideration the type of ice and the ice class of the vessel. Special information services based on satellite monitoring as well as reports from vessels and polar stations, presenting information on ice cover in tables and diagrams, can be used as the source of data on the ice situation along the route. The current paper proposes a pattern concept of route planning and notes the complexity of its implementation. Simplifying the problem by finding the shortest way of the route in the weighted graph is suggested, which is a conventional strategy in ship navigation. Possible approaches to developing a set of graph nodes and edges as well as weighing the graph edges are discussed. Some recommendations for reducing computational complexity of tasks are given. The paper is accompanied with calculations of vessel routes using the data on ice situation in the sea of Okhotsk. The given examples show that the ship's track is formed in such a manner that the traffic in the sea areas covered by ice is decreased. Following on from the results of calculating routes under various ice conditions, a conclusion is made about the possibility of solving the problem in this way.

1. Tam Ch. K., Bucknall R., Greig A. Review of collision avoidance and path planning methods for ships in close range encounters. Journal of Navigation. 2009;62(3):455–476.

2. Pershina L.A., Astreina L. S. Ship routing based on weather conditions. Ekspluatatsiya morskogo transporta. 2019;2(91):30–38. (In Russ.)

3. Veremei E.I., Sotnikova M. V. Optimal routing based on weather forecast. International Journal of Open Information Technologies. 2016;4(3):55–61. (In Russ.)

4. Akmaykin D.A., Khomenko D.B., Klueva S.F. Overview Features and Perspectives of Modern Automated Ship Route Planning Systems. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova. 2017;9(2):237–251. (In Russ.)

5. Akmaykin D.A., Bukin O. A., Grinyak V. M., Moskalenko M. A. Ships Route Planing with the Account of Dangerous Sea Waves. Morskiye intellektualʹnyye tekhnologii = Marine Intelligent Technologies. 2018;4–5(42):148–152. (In Russ.)

6. Varenichev A.A., Gromova M.P., Dugin G.S. The Leading Role of Northern Sea Way in the Development Liquefied Natural Gas Transportation. Transport: nauka, tekhnika, upravlenie. 2019;(7):65–70. (In Russ.)

7. Sobolevskaya E.Y., Glushkov S.V., Levchenko N.G. Architecture of Intelligent System of Organization of Arctic Maritime Cargo Transportation. Modelirovaniye, optimizatsiya i informatsionnyye tekhnologii = Modelling, optimization and information technologies. 2017;4(19):27. (In Russ.)

8. Sobolevskaya E.Y., Glushkov S.V., Levchenko N.G. Development of Information Intelligent System for the Organization and Management of Sea Cargo Transportation in Arctic Conditions – Setting of Mamdani Fuzzy Logic System. Ekspluatatsiya morskogo transporta. 2019;2(91):68–73. (In Russ.)

9. Andreeva E.V. Multi-Criteria Approach to The Problem of Choosing the Optimal Routes in the Waters of the Northern Sea Route. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova. 2021;13(3):399–408. (In Russ.)

10. Aleshin A.A., Kubrin S.S. Functional Scheme of Operative Route Optimization During Ice Navigation. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova. 2021;13(2):222–231. (In Russ.)

11. Pravila klassifikatsii i postroyki morskih sudov. Chast 1. Klassifikatsiya. No 2-020101-138. Rossiysky morskoy registr sudohodstva. 2021. (In Russ.)

12. Sotnikova M.V. Algorithms of Marine Ships Routing Taking into Account Weather Forecast. Vestnik Sankt Peterburgskogo universiteta. Prikladnaya matematika. Informatika. Protsessy upravleniya. 2009;(2):181–196. (In Russ.)

13. Wang H.B., Li X.B., Li P.F., Veremey E.I., Sotnikova M.V. Application of real-coded genetic algorithm in ship weather routing. Journal of Navigation. 2018;71(4):989–1010.

14. Nuriev R.A., Ershov A.A. Procedure for Choosing the Optimal Ocean Route When Gale. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S O. Makarova. 2021;13(5):625–635. (In Russ.)

15. Grinyak V.M., Akmaykin D.A., Lulko V.I. Ships Route Planning with Respect of Sea Wave Properties. Modelirovaniye, optimizatsiya i informatsionnyye tekhnologii = Modelling, Optimization and Information Technologies. 2018;6(4):469–483. (In Russ.)

16. Grinyak V.M., Shulenina A.V., Prudnikova L.I., Devyatisilnyi A.S. Ships Route Planning on Heavy-Traffic Marine Area. Modelirovaniye, optimizatsiya i informatsionnyye tekhnologii = Modelling, Optimization and Information Technologies. 2021;9(2):31–32. (In Russ.)

17. Gongxing W., Incecik A., Tezdogan T., Momchil T., Ling Chao W. Long-voyage route planning method based on multi-scale visibility graph for autonomous ships. Ocean Engineering. 2021;219:108242.

18. Grinyak V.M., Akmaykin D.A., Devyatisilnyi A.S. Assessment of the Prospects for Using Meteorological Satellite Data for Planning a Vessel Route in the Arctic Waters. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova. 2019;11(2):209–221. (In Russ.)

19. Grinyak V.M., Akmaykin D.A., Ivanenko Yu.S. Feasibility Study for Ship Trajectory Planning Problem Using Marine Weather Data from Satellites. Modelirovaniye, optimizatsiya i informatsionnyye tekhnologii = Modelling, Optimization and Information Technologies. 2017;2(17):15. (In Russ.)

20. Kasianov V.N., Evstigneev V.A. Grafy v programmirovanii: vizualizatsiya i primeneniye. Sankt Petersburg: BHV-Peterburg; 2003. (In Russ.)

21. Kuhlemann S., Tierney K. A genetic algorithm for finding realistic sea routes considering the weather. Journal of Heuristics. 2020;26:801–825.

22. Lin Y.-H., Fang M.-C., Yeung R.W. The optimization of ship weather-routing algorithm based on the composite influence of multi-dynamic elements. Applied Ocean Research. 2013;43:184–194.

23. Lu R., Turan O., Boulougouris E., Banks C., Incecik A. A semi-empirical ship operational performance prediction model for voyage optimization towards energy efficient shipping. Ocean Engineering. 2015;(110):18–28.

24. Lazarowska A. Ship’s trajectory planning for collision avoidance at sea based on ant colony optimization. Journal of Navigation. 2015;68(2):291–307.

25. Fedorenko K.V., Olovyannikov A.L. Research of the Main Parameters of the Genetic Algorithm for the Problem of Searching the Optimal Route. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova. 2017;9(4):714–723. (In Russ.)

26. Glushkov S.V., Sobolevskaya E.Y., Levchenko N.G. Formation of training sample for information intelligent system of organization and management of arctic sea cargo transportation. Morskiye intellektualʹnyye tekhnologii = Marine Intelligent Technologies. 2020;1–2(47):230–235. (In Russ.)

27. Titov A.V., Barakat L., Chanchikov V.A., Taktarov G.A., Kovalev O.P. Control systems of unmanned vessels. Morskiye intellektualʹnyye tekhnologii = Marine Intelligent Technologies. 2019;1–4(43):109–120. (In Russ.)

28. Karetnikov V.V., Kozik S.V., Butsanets A.A. Risks assessment of applying unmanned means of water transport in the water area. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S.O. Makarova. 2019;11(6):987–1002. (In Russ.)