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Maritime traffic complexity evaluation in the Yangtze River using AIS data

Advances in Maritime Technology and Engineering

Xu X.; Yan X.; Guedes Soares C.2024Taylor and Francis Group

Key information

Authors:

Xu X.; Yan X.; Wu B.; Teixeira A.P. (Ângelo Manuel Palos Teixeira); Guedes Soares C. (Carlos Guedes Soares)

Published in

2024

Abstract

Traffic complexity evaluation is an element of marine situation awareness that plays a critical role in ensuring navigation safety. This paper proposes a method for evaluating marine traffic flow complexity using AIS data that can be used by marine supervisors in vessel traffic service (VTS) centers to enhance the understanding of the marine traffic condition. The traffic flow complexity is evaluated in three steps, including data preprocessing, weight determination and traffic complexity modelling. First, abnormal AIS data are deleted and then the remaining data are synchronized. Second, the distance between all ship pairs is calculated using AIS data and an exponential function of the distances is adopted as weight to express the relationship among the ships. Third, the graph theory is introduced to describe marine traffic conditions, and the indicators edge density and strength are used to evaluate the complexity. The experimental results in a selected section of the Yangtze River show that the proposed method can quantitatively evaluate the marine traffic complexity and effectively strengthen the marine traffic condition situation assessment by the VTS operators.

Publication details

Authors in the community:

Publisher

Taylor and Francis Group

Title of the publication container

Advances in Maritime Technology and Engineering

Volume

1

First page or article number

159

Last page

164

ISBN

978-1-032-83099-5

Fields of Science and Technology (FOS)

other-engineering-and-technologies - Other engineering and technologies

Publication language (ISO code)

eng - English

Rights type:

Open access

Financing entity

Centro de Engenharia e Tecnologia Naval e Oceânica, Instituto Superior Técnico

Identifier for the funding entity: 52272422