Supervision of Multiple Remote Tower Centers: Evaluating a New Air Traffic Control Interface Based on Mental Workload and Eye Tracking
Remote air traffic control offers inexpensive and efficient service to multiple airports. Recent research shows that one remote air traffic control officer can safely control up to three low-traffic airports simultaneously. In a multiple remote tower center, airports can be flexibly allocated across air traffic control officers based on prospective traffic loads. The main task of the supervisor in such a center is balancing the workload of each air traffic control officer by allocating airports accordingly. This study analyzes the supervisor's visual attention during interaction with a planning tool for their daily tasks. Five use cases were identified as the main tasks of the supervisor representing a mixture of planned and unplanned events. A mixed methods within-subjects design was used to assess the workload and eye-movement patterns associated with each of these use cases. In total, 15 professional air traffic control officers participated in the study. Workload and eye movement were analyzed independently in relation to the use cases but also in combination with each other. Across all use cases, a small correlation between subjective workload ratings and fixation duration was found, supporting previous findings of fixation duration being associated with information processing. Transitions between areas of interest on the supervisor planning tool provided valuable insights into the layout design of future supervisor planning tools.
Authors
- Leo Julius Materne (ORCID: https://orcid.org/0009-0003-8303-4125)
- Maik Friedrich (ORCID: https://orcid.org/0000-0003-3742-2322)
Institutions
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Publication Details
- Journal
- IEEE Transactions on Human-Machine Systems
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1109/thms.2025.3527136
- Citations
- 3
- Primary Topic
- Human-Automation Interaction and Safety
- Type
- article
- Field-Weighted Citation Impact
- 7.32