Abnormal behavior recognition of inland river ferryboat

Journal article (2017)

Authors

L. Huang Wuhan University of Technology

Yi Liu Wuhan University of Technology

Yuan Qiao Wen Hubei Key Laboratory of Inland Shipping Technology, Wuhan University of Technology

Chunhui Zhou Wuhan University of Technology, Hubei Key Laboratory of Inland Shipping Technology

Fan Zhang Wuhan University of Technology

Anomaly detection Automatic identification system (AIS) Inland river ferryboat Ship behavior pattern Ship status

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Published Date

2017

Language

English

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Abstract

At present, the supervision mode of inland ferrying was conducted passively by mainly human analysis and judgement based on VTS and AIS, which is not favorable to reply increasingly serious situation of marine security supervision. The historical AIS data of the ferryboat was analyzed to explore its motion pattern and obtain the probability density spatial distribution of motion characteristics of location, course and speed by using the kernel density estimation. Then on this basis, the detection algorithm of the ferryboat abnormal behaviors was established for location and speed abnormity, and actual AIS data was used to verify the algorithm. Experimental results show that the proposed algorithm can accurately recognize the abnormal behaviors of the ferryboat, which is helpful to the marine supervision.