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Air traffic predictability framework – Development, performance evaluation and application

Author

Listed:
  • Tobaruela, Gonzalo
  • Fransen, Peter
  • Schuster, Wolfgang
  • Ochieng, Washington Y.
  • Majumdar, Arnab

Abstract

The performance of the Air Traffic Flow & Capacity Management (ATFCM) function relies fundamentally on the accuracy of air traffic predictability. Characterising this accuracy and assessing the potential benefits of increased accuracy is fundamental to enhance the performance of the Air Traffic Management (ATM) system and identifying areas that require improvement. This paper develops a framework to assess air traffic predictability. It validates the proposed framework with real operational data and applies it to the Maastricht Upper Area Control centre. The paper develops a methodology to assess the benefits of the deployment of enhanced predictability including capacity, resulting from improved operational concepts such as Airport-Collaborative Decision Making (A-CDM).

Suggested Citation

  • Tobaruela, Gonzalo & Fransen, Peter & Schuster, Wolfgang & Ochieng, Washington Y. & Majumdar, Arnab, 2014. "Air traffic predictability framework – Development, performance evaluation and application," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 48-58.
    • Handle: RePEc:eee:jaitra:v:39:y:2014:i:c:p:48-58
    DOI: 10.1016/j.jairtraman.2014.04.001
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    Citations

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    Cited by:

    1. Okwir, Simon & Ulfvengren, Pernilla & Angelis, Jannis & Ruiz, Felipe & Núñez Guerrero, Yilsy Maria, 2017. "Managing turnaround performance through Collaborative Decision Making," Journal of Air Transport Management, Elsevier, vol. 58(C), pages 183-196.
    2. Kang, Lei & Hansen, Mark & Ryerson, Megan S., 2018. "Evaluating predictability based on gate-in fuel prediction and cost-to-carry estimation," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 146-152.

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