疲劳对C-17进近和着陆性能影响的综合建模

IF 1 4区 心理学 Q4 PSYCHOLOGY, APPLIED International Journal of Aerospace Psychology Pub Date : 2023-01-02 DOI:10.1080/24721840.2022.2149526
Bella Z. Veksler, Megan B. Morris, M. Krusmark, G. Gunzelmann
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引用次数: 2

摘要

摘要目的当前的工作开发了C-17进近和着陆操作背景下的疲劳初始综合模型。具体而言,我们将生物数学疲劳模型与任务网络模型相结合,以估计飞行员的性能退化。背景疲劳风险管理是航空和飞行甲板操作中的一个关键过程,因为它对航空安全和飞行员健康有着巨大的影响。生物数学疲劳模型是一些航空疲劳风险管理程序中的有用工具,这些程序可以嵌入电子设备应用中。然而,这些工具在识别受疲劳影响的具体性能结果以及对个别飞行员的疲劳估计方面是有限的。整合计算认知模型和生物数学疲劳模型可以帮助解决这些问题。方法44名机组人员完成了这项研究,其中10人进行了33次着陆,并提供了相应的活动图数据和C-17性能指标。我们开发了C-17进近和着陆操作的任务网络模型,并基于机组人员的活动图数据进行了综合生物数学疲劳模型预测。然后,我们将该综合模型的预测与任务中的C-17性能指标进行了比较。结果我们成功地预测了襟翼、起落架和速度刹车的延迟。结论经过进一步的开发和验证,该集成模型可以在应用程序中实现,以提供飞行员疲劳和特定飞机操作预期性能的实时信息。
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Integrated Modeling of Fatigue Impacts on C-17 Approach and Landing Performance
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.
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CiteScore
2.80
自引率
7.70%
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