This paper presents a new method to facilitate integrating new vehicle traffic operations, operating with existing air traffic operations. The extensible traffic management (xTM) concept assumes that the new vehicles can operate in a dedicated Cooperative Area (CA) with minimal interaction with conventional air traffic and requiring minimal air traffic supervision. Our method assumes that a new xTM CA can be created when an underutilized airspace with little or no traffic can be identified. Our approach involves modeling airspace as a tree data structure and iteratively subdividing it into smaller cells, with underutilized airspace defined as any cells without flight tracks. The benefits of our approach include its applicability to all xTM scenarios, the ability to handle both 2D and 3D space using a unique tree data structure, and computational efficiency for key functions such as space decomposition, labeling of connected cells, and searching of cells containing a given point. By automatically searching for underutilized airspace based on operating air traffic patterns, we can optimize airspace utilization and improve air traffic management. Our proposed approach can quantitatively determine when and where to allow xTM operations in the National Airspace System.


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    Titel :

    Search for UnderUtilized Airspace for Extensible Traffic Management Operations Based on Air Traffic Patterns


    Beteiligte:
    Jinhua Li (Autor:in) / Min Xue (Autor:in) / Paul U Lee (Autor:in) / Priyank Pradeep (Autor:in)

    Kongress:

    AIAA Aviation Forum and Exposition ; 2023 ; San Diego, CA, US



    Erscheinungsdatum :

    2023-06-19


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch