Understanding ship following behavior in sea ice conditions is essential for safe navigation in the Arctic. In order to unveil the ship following behavior and dominated impact factors, this research studied the ship following navigation characteristics and behavior in the Arctic through a systematic data mining approach. Firstly, a data mining mechanism was developed to extract comprehensive ship following data from the 2022 Arctic AIS dataset, enabling a comprehensive analysis of ship-following behavior. Then, Sea Ice Thickness (SIT) and Sea Ice Concentration (SIC) data are extracted and spatiotemporally linked to the ship following data to reveal the influence of sea ice on the ship following speed and distance within formations. Finally, a quantitative analysis of ship following speeds and distances under varying ice conditions were analyzed. A total of 76 formations are recorded, with formations involving icebreaker being more common, predominantly from January to May in the central Kara Sea and southeast East Siberian Sea. Results revealed that SIT mainly affects ship following speed, while SIC predominantly influences following distance, with significant negative correlations observed in formations with or without an icebreaker. This research elucidates the ship formation characteristics and the influence of sea ice on ship following behavior, providing theoretical guidance for safe formation in the Arctic waters.
Research on Ship Following Behavior Based on Data Mining in Arctic Waters
IEEE Transactions on Intelligent Transportation Systems ; 26 , 5 ; 6778-6788
01.05.2025
8337452 byte
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Ship Behavior Recognition in Port Waters Based on Data Mining
Springer Verlag | 2025
|Online Contents | 2008
|Engineering Index Backfile | 1952
Research Plan for Arctic Ship Powering and Development
NTIS | 1977
|Engineering Index Backfile | 1952