Using Human-Machine Interaction Frequency as a Proxy Measure of Subjective Air Traffic Complexity

Subjective air traffic complexity scores have been used previously as a useful measure of air traffic controller workload. There were, however, difficulties in implementing such measurements for real-time workload assessment due to the extent of modifications needed on an operational ATM system. A solution is proposed here which requires only the minimum of HMI data to determine the subjective air traffic complexity. For this paper, an experiment has been conducted with licensed air traffic controllers who assessed air traffic complexity in real-time human-in-the-loop simulations. Simultaneously, basic human-machine interactions were recorded. Analysis of the simulation data showed that the human-machine interactions can be used, with some limitations, to detect increases in air traffic complexity and situations where the controller’s workload capacity is exhausted.