Quantifying pilot reaction time and workload in takeoff operations: A QN-MHP model approach

Accurate quantification of pilot reaction time and workload during takeoff is essential for understanding human performance in time-critical flight operations. Delayed reactions or excessive workload in takeoff operations can compromise operational performance and increase the risk of accidents. To address this issue, this study used the Queueing Network-Model Human Processor (QN-MHP) model to investigate how cue condition and rudder-control mode influence pilot reaction time and task-related subjective workload under four simulated takeoff conditions. A high-fidelity simulated flight experiment was conducted using X-Plane 11, and 10 pilot cadets participated. Results indicated that automatic-rudder conditions were associated with shorter response latencies than manual-rudder conditions. Response latencies also differed between the visual self-detection and standardised rotate-callout conditions. These findings are generally consistent with the predictions of the QN-MHP model, supporting its applicability for modelling pilot cognitive performance during simulated takeoff operations. Exploratory subjective ratings further indicated that automatic-rudder conditions were associated with lower perceived workload than manual-rudder conditions. Overall, this study provides theoretical and empirical support for understanding pilot cognitive performance during simulated takeoff tasks and may contribute to future training design and human-centered aviation research.