A method to estimate air traffic controller mental workload based on traffic clearances |
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| Institution: | 1. Imperial College London, Centre for Transport Studies, Department of Civil and Environmental Engineering, South Kensington Campus, London SW7 2AZ, United Kingdom;2. EUROCONTROL Maastricht Upper Area Control Centre, Horsterweg 11, 6199 AC Maastricht Airport, The Netherlands;1. Università degli Studi di Palermo, Dipartimento di Fisica e Chimica, Viale delle Scienze, Ed. 18, I-90128, Palermo, Italy;2. Deep Blue srl, P.zza Buenos Aires, Roma, Italy;3. University of Westminster, 35 Marylebone Road, London NW1 5LS, United Kingdom;4. Scuola Normale Superiore, Piazza dei Cavalieri 7, Pisa, Italy;5. Central European University, Center for Network Science, Nador 9, H-1051, Budapest, Hungary;6. Central European University, Department of Economics, Nador 9, H-1051, Budapest, Hungary;1. Smart City College, Beijing Union University, China;2. School of Electronics and Information Engineering, Beihang University, China;3. School of Engineering and Information Technology, University of New South Wales, Australia;1. RMIT University, Melbourne, Victoria 3001, Australia;2. Thales Australia Air Traffic Management, Melbourne, Victoria 3001, Australia |
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| 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. |
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| Keywords: | Air traffic control Mental workload Perceived complexity Workload estimation Maastricht Upper Area Control (MUAC) centre |
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