Models to predict operational loads of flight schedules

Area of Science:

• Aviation Psychology
• Human Factors Engineering
• Occupational Health

Background:

• Predicting operational load on aircrews during long-distance flights is crucial for safety and performance.
• Existing literature offers several conceptual models for assessing flight duty-related stress.

Purpose of the Study:

• To evaluate and compare different models for predicting aircrew operational load on a specific airline route.
• To introduce a novel approach for quantifying operational load by integrating key flight and crew factors.

Main Methods:

• Application of established operational load models to a scheduled long-distance flight duty pattern.
• Comparative analysis of relative and absolute difficulty grades assigned by different models to flight segments.
• Development of a new computable model incorporating duty period, night flying, transit numbers, layover, and time-zone transitions.

Main Results:

• High agreement was observed among various models when ranking flight segments by relative difficulty.
• Significant discrepancies emerged when models provided absolute classifications of flight segments (normal, heavy, severe).
• Mohler's model was identified as providing the most realistic load estimates based on observations.

Conclusions:

• While relative difficulty assessments align across models, absolute load classifications vary considerably.
• Mohler's model offers a reliable estimation of aircrew operational load.
• A comprehensive approach integrating duty period, night flying, transits, layover, and time-zone transitions provides a computable and essential measure of operational load.