Modeling pilot mental workload using information theory

被引:7
作者
Zhang, X. [1 ,2 ,3 ]
Qu, X. [1 ,2 ]
Xue, H. [3 ]
Zhao, H. [3 ]
Li, T. [3 ]
Tao, D. [1 ,2 ]
机构
[1] Shenzhen Univ, Coll Mechatron & Control Engn, Inst Human Factors & Ergon, Shenzhen, Peoples R China
[2] Shenzhen Univ, Key Lab Optoelect Devices & Syst, Minist Educ & Guangdong Prov, Shenzhen, Peoples R China
[3] Northwestern Polytech Univ, Sch Aeronaut, Xian, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Mental workload; Task complexity; Taxiing; pilot; Information theory; Shannon's Law; PHYSIOLOGICAL INDEXES; AIRPORT SURFACE; EYE ACTIVITY; PERFORMANCE; TASK; ADAPTATION; TRACKING; EEG;
D O I
10.1017/aer.2019.13
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
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.
引用
收藏
页码:828 / 839
页数:12
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