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.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Air traffic optimization on data-driven network flow model


    Beteiligte:
    Marzuoli, Aude (Autor:in) / Gariel, Maxime (Autor:in) / Vela, Adan E. (Autor:in) / Feron, Eric (Autor:in)


    Erscheinungsdatum :

    01.10.2011


    Format / Umfang :

    604608 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Air traffic optimization on data-driven network flow model

    Marzuoli, Aude / Gariel, Maxime / Vela, Adan et al. | IEEE | 2011

    Freier Zugriff

    Optimization Approach to Data-Driven Air Traffic Flow Management

    Diao, Xudong / Lu, Shan | Transportation Research Record | 2021




    Flow count data-driven static traffic assignment models through network modularity partitioning

    Roocroft, Alexander / Punzo, Giuliano / Ramli, Muhamad Azfar | Springer Verlag | 2025

    Freier Zugriff