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Modeling pilot mental workload using information theory

Published online by Cambridge University Press:  03 June 2019

X. Zhang
Affiliation:
Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China Key laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen, China School of Aeronautics, Northwestern Polytechnical University, Xi’an, China
X. Qu
Affiliation:
Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China Key laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen, China
H. Xue*
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an, China
H. Zhao
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an, China
T. Li
Affiliation:
School of Aeronautics, Northwestern Polytechnical University, Xi’an, China
D. Tao
Affiliation:
Institute of Human Factors and Ergonomics, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, China Key laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, Shenzhen University, Shenzhen, China

Abstract

Predicting mental workload of pilots can provide cockpit designers with useful information to reduce the possibility of pilot error and cost of training, improve the safety and performance of systems, and increase operator satisfaction. We present a theoretical model of mental workload, using information theory, based on review investigations of how effectively task complexity, visual performance, and pilot experience predict mental workload. The validity of the model was confirmed based on data collected from pilot taxiing experiments. Experiments were performed on taxiing tasks in four different scenarios. Results showed that predicted values from the proposed mental workload model were highly correlated to actual mental workload ratings from the experiments. The findings indicate that the proposed mental workload model appears to be effective in the prediction of pilots’ mental workload over time.

Type
Research Article
Copyright
© Royal Aeronautical Society 2019 

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References

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