Air Traffic Controller Competence Retention and Retention Modelling: a preliminary study
Air Traffic Controller Competence Retention and Retention Modelling: a preliminary study
Date
2022
Authors
Hove, P.E. ten
Tillema, G.H.J.
Eaglestone, J.
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
License Holder
© 2022 NLR
Licence Type
CC BY-NC-ND license
Sponsor
Abstract
Air Traffic Controller (ATCO) error can have a huge impact on flight safety, therefore preventing skill decay is essential. Training can be a good remedy, but training is expensive and sometimes unnecessary. Understanding how and when skill decay occurs is essential in personalising retention training. This preliminary study examines methods for measuring (military) ATCO skill decay. Experimental sessions were conducted with five military ATCOs in the MicroNav BEST Training Simulator. During each experiment session a complex approach control task, and a surveillance radar approach, were performed and both subjective- and objective data (i.e. simulator and eye-tracking data) was collected. Although the results showed no significant differences between the sessions, new insights into skill decay indicators were gained, including factors such as change in ATCO scan-patterns and the influence of ATCO experience (i.e. level and exposure) on the task.
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Keywords
Citation
Petra ten Hove, Guido Tillema, Jennifer Eaglestone, Air Traffic Controller Competence Retention and Retention Modelling: a preliminary study, Transportation Research Procedia, Volume 66, 2022, Pages 136-147, ISSN 2352-1465, https://doi.org/10.1016/j.trpro.2022.12.015.