A method of ship multi-constraint route planning based on AIS big data

Guangqiang Liu; Shengwei Li; Xinwei Zhou

doi:10.1117/12.2673554

22 May 2023 A method of ship multi-constraint route planning based on AIS big data

Guangqiang Liu, Shengwei Li, Xinwei Zhou

Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 1264003 (2023) https://doi.org/10.1117/12.2673554
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China

Abstract

In order to solve the problem of lack of reference to real ship trajectory in ship route planning, a method of ship multi-constraint route planning based on AIS (Automatic Identification System) big data is hereby proposed after analyzing existing route planning methods. The AIS feature trajectories generated in the preprocessing stage are clustered using Fuzzy Adaptive Density-Based Spatial Clustering of Application with Noise (FA-DBSCAN) to identify similar ships turning area. Under the constructed navigable grid chart environment model and multi-condition constraints, the ship route planning is realized by improving the ant colony algorithm. The simulation test results show that the planned route obtained using this method is provided with more advantages than other methods in terms of navigation cost, applicability and operating efficiency.

Citation Download Citation

Guangqiang Liu, Shengwei Li, and Xinwei Zhou "A method of ship multi-constraint route planning based on AIS big data", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 1264003 (22 May 2023); https://doi.org/10.1117/12.2673554

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