Pilot Workload Management for Single-Pilot Ops With e-Copilot

Single-pilot operations impose cognitive and procedural demands, particularly during abnormal events, airspace transitions, and communication-intensive flight segments. This study evaluated an ecopilot designed to manage workload by assisting with routine radio and checklist tasks while highlighting anomalies requiring pilot attention. In a flight simulation, 28 participants completed normal and abnormal scenarios under three conditions: baseline single-pilot operation, a rulebased e-copilot, and a predictive e-copilot using learned anomaly scoring. Outcomes included procedural deviations, radio timing, situation awareness, and startle recovery. The predictive e-copilot produced the greatest benefits, reducing procedural deviations by approximately 24% relative to baseline and improving recovery following unexpected events. The rule-based system also enhanced routine checklist and radio performance but was less effective during abnormal scenarios. Situation awareness remained stable across conditions, indicating that task offloading did not promote disengagement or complacency. Overall, predictive anomaly surfacing improved workload management while preserving pilot authority and supporting safer single-pilot performance.