Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

Dominik Filipiak (), Krzysztof Węcel (), Milena Stróżyna (), Michał Michalak and Witold Abramowicz ()
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Dominik Filipiak: Poznań University of Economics and Business
Krzysztof Węcel: Poznań University of Economics and Business
Milena Stróżyna: Poznań University of Economics and Business
Witold Abramowicz: Poznań University of Economics and Business

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2020, vol. 62, issue 5, No 4, 435-450

Abstract: Abstract The presented method reconstructs a network (a graph) from AIS data, which reflects vessel traffic and can be used for route planning. The approach consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The maneuvering points detection uses the CUSUM method and reduces the amount of data for further processing. The genetic algorithm with spatial partitioning is used for waypoints discovery. Finally, edges connecting these waypoints form the final maritime traffic network. The approach aims at advancing the practice of maritime voyage planning, which is typically done manually by a ship’s navigation officer. The authors demonstrate the results of the implementation using Apache Spark, a popular distributed and parallel computing framework. The method is evaluated by comparing the results with an on-line voyage planning application. The evaluation shows that the approach has the capacity to generate a graph which resembles the real-world maritime traffic network.

Keywords: Maritime traffic network; Vessel routing; Route planning; AIS; Maritime traffic graph; Waypoint discovery; Graph discovery; Artificial intelligence; Genetic algorithm (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s12599-020-00661-0

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