This study aims to first develop a successful taskloadmodel which is able to relate the controller’s interaction with theradar screen to the dynamical changes in air traffic patterns.Secondly, the study aims to examine whether i4D equipage, as aspecific notion of automation, contributes to an improvement inquantification of controller’s taskload model. Thirdly, in a morespecific approach the study intends to analyze to what extentcontrollers may or may not benefit from predictable situations atdense traffic conditions when exposed to higher automatedairspace environment. The model is applied on 18 data setsfeaturing different i4D-equipage levels. It compares controllers’taskload for three different scenarios between an en-route and aterminal sector.