Predicting Air Traffic Controller Workload

Abstract

Objective: Our study investigates whether trajectory uncertainty moderates the relationship between traffic conflict and workload. Furthermore, we examine if the indirect effect of traffic density on workload through traffic conflict is conditional on the presence of trajectory uncertainty. Background: Although it is widely accepted that uncertainty related to the future trajectory of an aircraft impacts air traffic controller decision making, little is known about how the presence of trajectory uncertainty impacts controller workload. A better understanding of the impact on controller workload can improve workload prediction models for en route air traffic control. Method: We collected data in a live operation environment, including workload ratings based on over-the-shoulder observations and real-time sector data. Hierarchical linear modeling was used to analyze the data. Results: Trajectory uncertainty interacts with traffic conflict in such a way that the positive relationship between traffic conflict and workload is strongest in the presence of trajectory uncertainty. Furthermore, we found that the mediating effect of traffic density through traffic conflict is conditional on the presence of trajectory uncertainty. Conclusion: Our results indicate that workload prediction tools that do not incorporate trajectory uncertainty may underestimate workload under conditions of trajectory uncertainty, leading to possible overload situations of air traffic controllers. Application: Sources that generate trajectory uncertainty, as well as their interaction effects with dynamic complexity metrics, should be acknowledged in workload prediction models to increase the predictive power of these models. Implications for future air traffic management operations as envisioned by SESAR and NextGen are discussed.