Bella Z. Veksler, Megan B. Morris, M. Krusmark, G. Gunzelmann
{"title":"Integrated Modeling of Fatigue Impacts on C-17 Approach and Landing Performance","authors":"Bella Z. Veksler, Megan B. Morris, M. Krusmark, G. Gunzelmann","doi":"10.1080/24721840.2022.2149526","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":41693,"journal":{"name":"International Journal of Aerospace Psychology","volume":"33 1","pages":"61 - 78"},"PeriodicalIF":1.0000,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Aerospace Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1080/24721840.2022.2149526","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PSYCHOLOGY, APPLIED","Score":null,"Total":0}
引用次数: 2
Abstract
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.