Affiliation:
1. School of Science, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
2. Key Laboratory of High Impact Weather (Special), China Meteorological Administration, Changsha 410073, China
3. College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China
Abstract
In this study, a new route planning model is proposed to help ocean-going ships avoid dangerous weather conditions and ensure safe ship navigation. First, we integrate ocean-going ship vulnerability into the study of the influence of meteorological and oceanic factors on navigational risk. A multi-layer fuzzy comprehensive evaluation model for weather risk assessment is established. A multi-objective nonlinear route planning model is then constructed by comprehensively considering the challenges of fuel consumption, risk, and time during ship navigation. The International Maritime Organization (IMO) guidelines are highlighted as constraints in the calculations, and wind, wave, and calm water resistance to ships in the latest ITTC method is added to the fuel consumption and sailing time in the objective function. Finally, considering the large amount of data required for ocean voyages, the bidirectional A* algorithm is applied to solve the model and reduce the planning time. Furthermore, our model is applied to the case of an accident reported in the Singapore Maritime Investigation Report, and the results show that the model-planned route is very close to the original planned route using the Towing Manual, with an average fit of 98.22%, and the overall meteorological risk of the model-planned route is 11.19% smaller than the original route; our model can therefore be used to plan a safer route for the vessel. In addition, the importance of risk assessments and the IMO guidelines as well as the efficiency of the bidirectional A* algorithm were analyzed and discussed. The results show that the model effectively lowers the meteorological risk, is more efficient than the traditional route planning algorithm, and is 86.82% faster than the Dijkstra algorithm and 49.16% faster than the A* algorithm.
Reference44 articles.
1. Wang, S., Yin, J., and Khan, R.U. (2020). The multi-state maritime transportation system risk assessment and safety analysis. Sustainability, 12.
2. Overview of definitions of maritime safety, safety at sea, navigational safety and safety in general;Formela;TransNav Int. J. Mar. Navig. Saf. Sea Transp.,2019
3. Numerical simulation of ship navigation in rough seas based on ECMWF data;Vinayak;Brodogradnja,2021
4. Ship route and speed multi-objective optimization considering weather conditions and emission control area regulations;Ma;Marit. Policy Manag.,2021
5. Multi-criteria route planning with risk contour map for smart navigation;Jeong;Ocean Eng.,2019