Pupillometry to assess Air Traffic Controller workload through the Mental Workload Model

Abstract

The introduction of automation in Air Traffic Management (ATM) implies a change in the Air Traffic Controller (ATCo) mental workload. In order to assess this impact, CRIDA is developing a mental workload model based on Wickens's and McCarley's Theories [1]. This model estimates the expected workload in terms of ATCo cognitive resource demand, which is defined as the central processing (Comprehension, Strategic Thinking, Decision Making) load in terms of perception (visual & auditory), and response (Execution: manual & verbal) required to perform a task in a safe and efficient manner.The use of this Mental Workload Model would allow the analysis on how the automation function reallocation between human and system impacts the related cognitive processes and mental workload.To achieve this goal the Mental Workload Model needs to be calibrated using both objective and subjective measurements of workload. As recent research in neuroscience has shown, there is a relationship between the pupillary responses and the mental activity. Specifically, they have revealed a tight correlation between the increase of the locus coeruleus activity and the pupillary dilation [2].Based on this approach, the main scope of this paper is to address the refinement and calibration of the Mental Workload Model through the pupil diameter measures collected during Real Time Simulations (RTS), proving first the correlation between the pupil measurements and workload. This paper reflects a preliminary study in the ATC domain that uses pupillometry to measure mental activity and therefore mental workload [3,4]. It also presents some results from an on-going research program aimed to validate and refine an ATCo's Mental Workload Model developed by CRIDA.