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Simulation-based UAS Swarm Selection for Monitoring and Detection of Migrant Border Crossings

By Caleb M. Harris, Max-Daniel Sokollek, Luis Salas Nunez, J.T. Valco, Michael G. Balchanos and Dimitri N. Mavris

Abstract

The European migration crisis reached critical levels in 2015 due to a major influx of migrants taking the journey across the Mediterranean to Italy, Greece, and other European coasts. Migration flow rates across the Mediterranean have dropped in recent years, but fatalities have increased and border pressure is still high. Recent operations by local governments, international agencies, and NGO organizations have saved many lives and improved data collection practices, yet they have not been fully successful in responding to the high volume of travel and unexpected rate spikes in migrant trips. Different Operational Constructs and asset strategies have been studied resulting in relevant organizations investing in Unmanned Aerial Systems (UAS) for monitoring and detection. However, many questions about the most effective deployment of these assets still remain. This study is centered on the development of a modeling and simulation environment, as well as a decision support tool for conducting system-of-systems comparisons of UAS swarm and surface fleet asset combinations. The environment is an agent-based simulation built in the In-House tool Janus, which leverages the NASAWorld-Wind SDK. The simulation tool and dashboard provide a trade-off environment for parametric analysis of swarm capabilities. A case study is performed for operations by the Italian Coast Guard off the coast of Libya. Results confirm the success of implementing UAS and coordinated swarm systems. Further analysis examines the trade-off of mission effectiveness and cost, with consideration of the resilience and robustness of the system-of-systems

Topics: Unmanned Aerial Systems (UAS), Swarms, Monitoring and detection
Publisher: 'American Institute of Aeronautics and Astronautics (AIAA)'
Year: 2018
DOI identifier: 10.2514/6.2018-3504
OAI identifier: oai:smartech.gatech.edu:1853/61917
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