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A method to estimate air traffic controller mental workload based on traffic clearances

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  • Tobaruela, Gonzalo
  • Schuster, Wolfgang
  • Majumdar, Arnab
  • Ochieng, Washington Y.
  • Martinez, Luis
  • Hendrickx, Peter

Abstract

Workload estimation is a complex domain which has been investigated extensively over the years. Past estimation techniques have focused on measuring workload directly from the air traffic controllers (ATCOs) or inferring it from traffic factors. The limitations of these techniques are interfering into the ATCO job and not being able to capture the differences amongst individual ATCOs respectively. This paper presents a novel technique overcoming these limitations, able to accurately estimate the workload experienced by the ATCO based exclusively on the clearances provided to air traffic. The technique, which was calibrated for the EUROCONTROL Maastricht Upper Area Control (MUAC) Centre, thereby has the potential to more accurately estimate actual airspace capacity. It is independent of the level of system automation and therefore applicable not only with the current ATM system, but also in the anticipated future highly automated environments as well as during the transition period. The paper discusses potential applications such as real time monitoring of operational workload and post-operations identification of sector workload imbalances. Both can contribute towards enhancing the performance of the ATM system.

Suggested Citation

  • Tobaruela, Gonzalo & Schuster, Wolfgang & Majumdar, Arnab & Ochieng, Washington Y. & Martinez, Luis & Hendrickx, Peter, 2014. "A method to estimate air traffic controller mental workload based on traffic clearances," Journal of Air Transport Management, Elsevier, vol. 39(C), pages 59-71.
    • Handle: RePEc:eee:jaitra:v:39:y:2014:i:c:p:59-71
    DOI: 10.1016/j.jairtraman.2014.04.002
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    References listed on IDEAS

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    1. Majumdar, Arnab & Ochieng, Washington Yotto & Bentham, James & Richards, Martyn, 2005. "En-route sector capacity estimation methodologies: An international survey," Journal of Air Transport Management, Elsevier, vol. 11(6), pages 375-387.
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    Cited by:

    1. Bongo, Miriam F. & Alimpangog, Kissy Mae S. & Loar, Jennifer F. & Montefalcon, Jason A. & Ocampo, Lanndon A., 2018. "An application of DEMATEL-ANP and PROMETHEE II approach for air traffic controllers’ workload stress problem: A case of Mactan Civil Aviation Authority of the Philippines," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 198-213.
    2. Kearney, Peter & Li, Wen-Chin, 2018. "Multiple remote tower for Single European Sky: The evolution from initial operational concept to regulatory approved implementation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 15-30.
    3. Ibáñez-Gijón, Jorge & Travieso, David & Navia, José A. & Montes, Aitor & Jacobs, David M. & Frutos, Patricia L., 2023. "Experimental validation of COMETA model of mental workload in air traffic control," Journal of Air Transport Management, Elsevier, vol. 108(C).
    4. Ohneiser, Oliver & Helmke, Hartmut & Shetty, Shruthi & Kleinert, Matthias & Ehr, Heiko & Murauskas, Šarūnas & Pagirys, Tomas, 2021. "Prediction and extraction of tower controller commands for speech recognition applications," Journal of Air Transport Management, Elsevier, vol. 95(C).

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