Ship Behavior Pattern Analysis Based on Graph Theory: A Case Study in Tianjin Port
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Published:2023-11-24
Issue:12
Volume:11
Page:2227
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ISSN:2077-1312
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Container-title:Journal of Marine Science and Engineering
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language:en
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Short-container-title:JMSE
Author:
Yu Hongchu12ORCID, Bai Xinyu1, Liu Jingxian123
Affiliation:
1. School of Navigation, Wuhan University of Technology, Wuhan 430063, China 2. Hainan Institute, Wuhan University of Technology, Sanya 572025, China 3. Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China
Abstract
With the rapid development of the global economy and trade, the number of ships serving ports in China is increasing continuously. Port traffic is becoming busier, and ship behavior is more complex and changeable. The analysis of ship behavior patterns in port waters has become an urgent problem to improve the efficiency and safety of port areas. In this paper, through the full integration of ship trajectory and port geographic information, the behavior chain of a single ship across the whole process of entering and exiting the port is identified. The traffic complexities and dynamics can be further analyzed by grouping the movement patterns of large ships. Based on graph theory, the port areas can be described as a transportation network in which functional areas are nodes and fairways between different areas are edges. The traffic can be analyzed through the network structure characteristics, such as node degree, node weight, and edge weight, and by their similarities and differences. This methodology provides a quantitative analysis for exploring the behavior patterns of large ships as well as the various traffic complexities. A case study in Tianjin Port has been conducted to verify the proposed model. The results show that it can accurately analyze a ship behavior’s regularity, occasion, and correlation. It provides a theoretical reference for the port to schedule and formulate emergency plans.
Funder
National Natural Science Foundation of China Open Fund Project of the State Key Laboratory of Surveying, Mapping and Remote Sensing Information Engineering Young Elite Scientists Sponsorship Program by China Association for Science and Technology National Key Research and Development Program Institute Local Cooperation Project of The Chinese Academy of Engineering
Subject
Ocean Engineering,Water Science and Technology,Civil and Structural Engineering
Reference32 articles.
1. Oumimoun, B., Nahiri, L., Idmouida, H., Addaim, A., Guennoun, Z., and Minaoui, K. (2022, January 9–10). Software Defined AIS Receiver Implementation Based on RTL-SDR and GNU Radio. Proceedings of the 2022 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob), Bandung, Indonesia. 2. Billah, M.M., Zhang, J., and Zhang, T. (2022). A Method for Vessel’s Trajectory Prediction Based on Encoder Decoder Architecture. J. Mar. Sci. Eng., 10. 3. The Piraeus AIS dataset for large-scale maritime data analytics;Tritsarolis;Data Brief,2022 4. Evmides, N., Odysseos, L., Michaelides, M.P., and Herodotou, H. (2022, January 6–9). An Intelligent Framework for Vessel Traffic Monitoring using AIS Data. Proceedings of the 2022 23rd IEEE International Conference on Mobile Data Management (MDM), Paphos, Cyprus. 5. Iphar, C., Le Berre, I., Napoli, A., and Foulquier, É. (2023, January 24–28). Port call extraction and characterisation from maritime navigational data: An application to the Lesser Antilles. Proceedings of the AGILE 2023 Conference, Orlando, FL, USA.
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