Modeling and Analysis of Controller’s Taskload in Different Predictability Conditions

This study aims to first develop a successful taskload model which is able to relate the controller’s interaction with the radar screen to the dynamical changes in air traffic patterns. Secondly, the study aims to examine whether i4D equipage, as a specific notion of automation, contributes to an improvement in quantification of controller’s taskload model. Thirdly, in a more specific approach the study intends to analyze to what extent controllers may or may not benefit from predictable situations at dense traffic conditions when exposed to higher automated airspace environment. The model is applied on 18 data sets featuring different i4D-equipage levels. It compares controllers’ taskload for three different scenarios between an en-route and a terminal sector. Keywords; Human-automation interaction; Air Traffic Controller (ATCO) taskload; airspace complexity; dynamic density