Title: Prediction of ships' position by analysing AIS data: an artificial intelligence approach

Authors: Leonardo Vanneschi; Mauro Castelli; Alessandro Re

Addresses: NOVA IMS, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal ' NOVA IMS, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal ' NOVA IMS, Universidade Nova de Lisboa, 1070-312, Lisboa, Portugal

Abstract: Maritime domain awareness deals with the situational understanding of maritime activities that could impact security, safety, the economy, or the environment. Nowadays, with the constant increase in maritime traffic, navigation security has become one of the most relevant and challenging issues in the maritime domain. This growth of maritime traffic has led to technological advances and new maritime regulations aiming to boost the safety of navigation. In that vein, use of the automatic identification system (AIS), a maritime safety and vessel traffic system, is now imposed by the International Maritime Organization. The system broadcasts position reports and short messages with information about a ship and its voyage (vessel identity, position, speed, course and destination). In this paper, a computational intelligence system able to predict the future position of a vessel using AIS data is proposed. The system is based on a recently defined variant of genetic programming that integrates semantic awareness into the search process. This system is compared with other state-of-the-art computational intelligence methods, showing its suitability for addressing the problem at hand.

Keywords: maritime awareness; navigation safety; AIS data.

DOI: 10.1504/IJWET.2017.088389

International Journal of Web Engineering and Technology, 2017 Vol.12 No.3, pp.253 - 274

Available online: 01 Dec 2017

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