Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm

The scientific article of the team of the Department of Information Systems has been published in the BISE journal. The journal’s Impact Factor for 2019 was 5.837 and the five-year impact factor was 7.361. Authors of the work: Dominik Filipiak, Krzysztof Węcel, Milena Stróżyna, Michał Michalak, Witold Abramowicz.

The presented in the paper method reconstructs a network (a graph) from AIS (Automatic Identification System) data, which reflects vessel traffic and can be used for route planning. Authors proposed an approach that consists of three main steps: maneuvering points detection, waypoints discovery, and edge construction. The approach aims at advancing the practice of maritime voyage planning, which is typically done manually by a ship’s navigation officer. The authors demonstrated the results of the implementation using Apache Spark, a popular distributed and parallel computing framework. The method was evaluated by comparing the results with an on-line voyage planning application. The evaluation showed that the approach has the capacity to generate a graph which resembles the real-world maritime traffic network.

Article in open access is available on the Springer website: link.springer.com/article/10.1007/s12599-020-00661-0