COMETA: An Air Traffic Controller’s Mental Workload Model for Calculating and Predicting Demand and Capacity Balancing

In ATM (Air Traffic Management), traffic and environment are not important by themselves. The most important factor is the cognitive work performed by the air traffic controller (ATCo). As detailed mental pictures can overcome ATCo’s limited attentional resources (causing Mental Overload), she/he can use internal strategies called abstractions to mitigate the cognitive complexity of the control task. This paper gathers the modelling, automation and preliminary calibration of the Cognitive Complexity concept. The primary purpose of this model is to support the ATM planning roles to detect imbalances and make decisions regarding the best DCB (Demand and Capacity Balancing) measures to resolve hotspots. The four parameters selected that provide meaningful operational information to mitigate cognitive complexity are Standard Flow Interactions, Flights out of Standard Flows, Potential Crossings and Flights in Evolution. The model has been integrated into a DCB prototype within the SESAR (Single European Sky ATM Research) 2020 Wave 1 during Real Time Simulations.