Model-Based Human Systems Integration for Evaluating Pilot Performance in Simulated Engine Malfunction Emergencies

Loss-of-engine emergencies in single-engine aircraft require rapid pilot response to achieve optimal glide performance, often under conditions not addressed by flight-manual data. This study applied Model-Based Human Systems Integration (MBHSI) to diagnose pilot performance and workload during unanticipated flameout approaches in a high-fidelity F-16 simulation. Pilots were unaware of failure timing and were required to manage energy state, airspeed, and navigation in real time. Three cohorts were evaluated with increasing levels of glide-performance cueing: a baseline condition, verbal guidance, and a tablet-based pilot–vehicle interface. Results demonstrated substantial performance variability driven by early energy-management decisions and the associated human performance resource demands. Pilots provided with real-time, weight-adjusted best-glide guidance via the tablet interface achieved significantly greater glide distance and improved touchdown performance compared to both baseline and verbally guided conditions. MBHSI analysis revealed that these improvements resulted from a reduction in task-specific human performance resource demand, rather than increased pilot effort or subjective workload tolerance. These findings demonstrate that MBHSI provides an objective, resource-based method for diagnosing workload and evaluating decision-aid effectiveness and offers an evidence-based approach for improving system-level performance and survivability during time-critical engine-out flight emergencies.