Analyzing Fatigue in Air Traffic Controller Trainees

To detect the fatigue status of air traffic controllers before duty and better manage on-the-job fatigue risk, this study proposes a convenient and effective pre-shift fatigue assessment method. A cohort of controller cadets was examined, using average reaction time, the standard deviation of reaction time, and the fastest 10% reaction time from a psychomotor vigilance test (PVT) as indicators of fatigue. These indicators were combined with self-reported MFI-16 fatigue scale scores to establish a quantitative relationship between fatigue level and each metric, allowing calculation of a comprehensive fatigue index for each cadet. This quantified fatigue index was then fitted against control-aptitude test scores to develop a regression model. An experimental condition involving 24 h of sleep deprivation was used to generate data for model development and validation. Results showed strong correlations between PVT metrics (average reaction time, reaction time variability, and fastest 10% reaction time) and fatigue scale scores. The resulting fatigue index model demonstrated good agreement between predicted and measured control-aptitude test scores. This study provides a theoretical foundation for a practical fatigue detection and early-warning method for air traffic controllers, offering significant value for reducing safety risks and enhancing civil aviation safety.