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True Experiments

Integrated Modeling of Fatigue Impacts on C-17 Approach and Landing Performance

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ABSTRACT

Objective

The current effort develops an initial integrated model of fatigue in the context of C-17 approach and landing operations. Specifically, we integrate a biomathematical fatigue model with a task network model to estimate pilot performance degradation.

Background

Fatigue risk management is a critical process in aviation and flight deck operations, given its dramatic impact on aviation safety and pilot health. Biomathematical fatigue models are useful tools in several aviation fatigue risk management programs that can be embedded in electronic device applications. However, these tools are limited in terms of identifying specific performance outcomes affected by fatigue, as well as individualizing fatigue estimates to individual pilots. Integrating computational cognitive models and biomathematical fatigue models can help address these issues.

Methods

Forty-four aircrew members completed the study with 10 performing 33 landings with sets of corresponding actigraph data and C-17 performance metrics. We developed a task network model of C-17 approach and landing operations and integrated biomathematical fatigue model predictions based on actigraph data from the aircrew. We then compared predictions from this integrated model with C-17 performance metrics from the missions.

Results

We successfully predicted delays in setting flaps, landing gear, and engaging the speed brake.

Conclusion

After further development and validation, this integrated model can be implemented within an application to provide real-time information on pilot fatigue and expected performance on specific aircraft operations.

Acknowledgments

The opinions expressed herein are solely those of the authors and do not necessarily represent the opinions of the United States Government, the U.S. Department of Defense, the U.S. Air Force, or any of their subsidiaries or employees. Portions of the current effort were reported in a paper in the proceedings of the 18th annual meeting of the International Conference on Cognitive Modelling. We would like to thank the Air Mobility Command Military Flight Operations Quality Assurance program for providing C-17 data and Air Mobility Command for providing feedback on the paper. Distribution A. Approved for public release. Case number: AFRL-2022-4253.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Notes

1. Readers should note that the specific implementation of the scheduling tool used by Air Mobility Command is proprietary. As a result, there might be slight differences in performance effectiveness estimates based on the specific versions of these tools.

Additional information

Funding

This work was partially supported by the Defense Health Agency’s Joint Program Committee on Military Operational Medicine [Fatigue Simulations for Single Pilot Aircraft Operations, 2016-2018]. This funding source had no involvement in the effort.

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