Trajectory Mining and Routing: A Cross-Sectoral Approach

Author:

Kaklis Dimitrios12,Kontopoulos Ioannis1ORCID,Varlamis Iraklis1ORCID,Emiris Ioannis Z.3ORCID,Varelas Takis2

Affiliation:

1. Harokopio Department of Informatics and Telematics, School of Digital Technology, University of Athens, 176 76 Kallithea, Greece

2. Danaos Shipping Co., 185 36 Attica, Greece

3. Athena Research Centre, 151 25 Marousi, Greece

Abstract

Trajectory data holds pivotal importance in the shipping industry and transcend their significance in various domains, including transportation, health care, tourism, surveillance, and security. In the maritime domain, improved predictions for estimated time of arrival (ETA) and optimal recommendations for alternate routes when the weather conditions deem it necessary can lead to lower costs, reduced emissions, and an increase in the overall efficiency of the industry. To this end, a methodology that yields optimal route recommendations for vessels is presented and evaluated in comparison with real-world vessel trajectories. The proposed approach utilizes historical vessel tracking data to extract maritime traffic patterns and implements an A* search algorithm on top of these patterns. The experimental results demonstrate that the proposed approach can lead to shorter vessel routes compared to another state-of-the-art routing methodology, resulting in cost savings for the maritime industry. This research not only enhances maritime routing but also demonstrates the broader applicability of trajectory mining, offering insights and solutions for diverse industries reliant on trajectory data.

Publisher

MDPI AG

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