Towards safer air traffic: Optimizing ATC controller workload by simulation with reduced set of parameters

The workload of air traffic controllers plays a crucial role in the safety and efficiency of air traffic as it is the prime factor to determine airspace capacity. Workload is the result of traffic complexity which can be described by different sets of parameters. In order to find a small, yet reliable set of complexity parameters that describe controller workload in the Hungarian Air Traffic Control system, a study with multiple steps was conducted and the results are presented in this paper. Information on the most important complexity factors was aquired from experts through interviews and questionnaires and as a result, different sets of parameters were created. To validate the method for gathering information as well as the applicability of complexity factors for airspace capacity estimation, a neural network based model was used. The results indicate that even smaller sets of parameters can be helpful in estimating workload.