Relationship of Individual Pilot Factors to Simulated Flight Performance

general aviation;pilots;CogScreen-AE;flight performance;working memory;processing speed;tracking;experience;age

Tolton, Rani G. ; Griffiths, Robin ; Herdman, Chris

University of Otago

关键词: general aviation;    pilots;    CogScreen-AE;    flight performance;    working memory;    processing speed;    tracking;    experience;    age;   

Others  :  https://ourarchive.otago.ac.nz/bitstream/10523/4977/1/ToltonRaniG2014MHealSc.pdf

美国|英语

来源: Otago University Research Archive

【 摘 要 】

Introduction:Requirements for greater cognitive skills have increased with expanding complexity of aircraft and the flying environment.The aim of this research was to investigate the relationship of age, cognition, education, experience, and income to simulated flight performance in general aviation pilots.Method:Fifty-four pilots, aged 21 to 79 years, flew a Cessna 172 simulator in low and high workload conditions.Flight performance was determined by altitude, heading, and speed deviations on the downwind portion of the ;;perfect” circuit.CogScreen-AE, a computerized cognitive battery, was used to measure pilot working memory, processing speed, and visual tracking.Results:In the low workload condition, older pilots did not perform as well as the younger pilots, r = -0.406, p = 0.002. In the high workload condition, there was a trend for older pilots not to perform as well as younger pilots but this was not significant, r = -0.253, p = 0.065.Significant contributions by working memory, visual tracking, and expertise determined flight performance in the low workload condition model, F = (8, 45) = 6.457, R2 = 0.496, p < 0.001.In the high workload condition, experience was the only significant contributor with working memory and processing speed adding variance to the model, F = (9, 44) = 2.627, R2 = 0.350, p = 0.016.Logistic Regression Probability Value (LRPV), a value obtained from the CogScreen-AE and often used to determine flight performance, correlated significantly in the high difficulty condition only but was not predictive of significant variance in the final linear regression model.Secondary analysis showed expertise had an enhancing effect in moderating between working memory and flight performance.Conclusion:This study revealed working memory, processing speed, tracking abilities as well as expertise and age are some of the factors influencing general aviation flight performance in varied conditions.LRPV which is used as an indicator for flight performance was not a predictive factor for general aviation pilots.