TTMRN
A topological-geometric two-layer maritime route network modeling for ship intelligent navigation
Chunhui Zhou (Wuhan University of Technology, China Laboratory of Transport Pollution Control and Monitoring Technology, Hubei Key Laboratory of Inland Shipping Technology)
Jiale Xiang (Wuhan University of Technology, Hubei Key Laboratory of Inland Shipping Technology)
Hongxun Huang (Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology)
Yi Yan (Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology)
Liang Huang (Wuhan University of Technology, TU Delft - Technology, Policy and Management)
Yuanqiao Wen (Wuhan University of Technology, National Engineering Research Center for Water Transport Safety)
Changshi Xiao (Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology)
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Abstract
The construction of maritime route networks holds significant importance for autonomous navigation of vessels. In this study, a two-layer maritime route network modeling method based on huge amounts of ship trajectory data was proposed. Firstly, we introduce a novel method for extracting nodes of the marine route network, which identifies feature points in ship trajectories through clustering. Secondly, we use a spatial computing method to transform ship trajectory data into a sequence of waypoint regions and establish a node connection matrix to realize the nodes' connection of the topological layer route network. And routes are extracted between waypoint regions to characterize the connection relationship of the geometric layer network. Finally, by connecting nodes of the topological layer with the support of the connection matrix and waypoint regions of the geometric layer with the route, the two-layer maritime route network that combines topological and geometric layers is constructed. The proposed method was applied to the waters of Vancouver, successfully constructing a topological-geometric two-layer maritime route network. Overall, the proposed method is beneficial for improving the safety and efficiency of autonomous navigation of ships, and has a positive impact on the development of smart shipping industry.