Air traffic optimization on data-driven network flow model

Aude Marzuoli, Maxime Gariel, Adan E. Vela, Eric Feron

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


This paper presents a new framework for Traffic Flow Management and Airspace Health Monitoring based on data-driven approach for air traffic flows modeling using historical data. The large-scale 3-dimensional flow network of the Cleveland center airspace provides valuable insight on airspace complexity. A linear formulation of the Traffic Flow Management Problem is proposed, taking into account estimations of controller workload based on flow geometry. Preliminary results for the problem are discussed, pointing out clues for further research. © 2011 IEEE.
Original languageEnglish (US)
Title of host publicationAIAA/IEEE Digital Avionics Systems Conference - Proceedings
StatePublished - Dec 28 2011
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2021-02-18


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