Assessment of pilot workload in flight simulation using pupillometry

In realistic civil flight operations, pilots must continuously manage multiple concurrent demands, making cognitive workload analysis essential to understand how task complexity and simulated emergencies can impact performance and situational awareness. Analyzing cognitive workload is crucial not only for interpreting pilot performance but also for informing the design of training protocols, task scenarios, and human-machine interfaces that mitigate overload and improve safety in civil operations. Throughout the last decades, multiple tools for workload evaluation were introduced, with the help of specialized instrumentation such as the Electroencephalogram data collection (EEG), Infrared Spectroscopy (IRS), heart rate variability, and pupillometry analysis. This thesis focuses its content on the last measurement technique – in particular, it aims to provide a further interpretation of cognitive workload measurements throughout a specific experiment, consisting of a series of tasks to be performed by human test subjects while operating a Cessna 172 in a Flight Simulator realistic scenario, with the help of a physical simulator control interface and a VR headset with eye-tracking capabilities in order to successfully track and analyze pupil diameter variations during the experiment. The major functionalities of the flight simulator to further improve realism were exploited, such as realistic photoscenery implementation through satellite imagery (orthophotos) and realistic scenarios implementation for task management and real emergency simulation. One of the main purposes of this project is to validate a measurement technique for cognitive workload evaluation, therefore supporting design activities by looking for the most demanding flight conditions for a human operator. The results of this project could help to improve user interfaces in both simulation and real-life layouts, ultimately increasing the overall safety of civil aviation.