With respect to the ergonomic evaluation and optimization in the mental task design of the aircraft cockpit display interface, the experimental measurement and theoretical modeling of mental workload were carried out under flight simulation task conditions using the performance evaluation, subjective evaluation and physiological measurement methods. The experimental results show that with an increased mental workload, the detection accuracy of flight operation significantly reduced and the reaction time was significantly prolonged; the standard deviation of R-R intervals (SDNN) significantly decreased, while the mean heart rate exhibited little change; the score of NASA_TLX scale significantly increased. On this basis, the indexes sensitive to mental workload were screened, and an integrated model for the discrimination and prediction of mental workload of aircraft cockpit display interface was established based on the Bayesian Fisher discrimination and classification method. The original validation and cross-validation methods were employed to test the accuracy of the results of discrimination and prediction of the integrated model, and the average prediction accuracies determined by these two methods are both higher than 85%. Meanwhile, the integrated model shows a higher accuracy in discrimination and prediction of mental workload compared with single indexes. The model proposed in this paper exhibits a satisfactory coincidence with the measured data and could accurately reflect the variation characteristics of the mental workload of aircraft cockpit display interface, thus providing a basis for the ergonomic evaluation and optimization design of the aircraft cockpit display interface in the future. ª 2014 Production and hosting by Elsevier Ltd. on behalf of CSAA & BUAA.

The present study attempted to establish an effective discrimination and prediction model that can be applied to evaluate mental workload changes in human-machine interaction processes on aircraft flight deck. By adopting a combined measure based on primary task measurement, subjective measurement and physiological measurement, this study developed both experimental measurement and theoretical modeling of mental workload under flight simulation task conditions. The experimental results showed that, as the mental workload increased, the peak amplitude of Mismatch negativity (MMN) was significantly increased, SDNN (the standard deviation of R-R intervals) was significantly decreased，the number of eye blink was decreased significantly. Finally, a comprehensive mental workload discrimination and prediction model for the aircraft flight deck display interface was constructed by the Bayesian Fisher discrimination and classification method. The model's accuracy was checked by original validation method. When comparing the prediction and discrimination results of this comprehensive model with that of single indices, the former showed much higher accuracy.

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According to the analysis of the main influencing factors of human errors in the aircraft cockpit and the establishment of the system dynamics model, the prediction and evaluation of the human errors causes are realized. The study provides a kind of research method and scientific basis for solving the problems of human errors in the aircraft cockpit. The simulation results show that the system dynamics model built for human errors analysis of the aircraft cockpit can make a mid long term prediction of the prevention level for human errors, and the prediction error is less than 10% compared with the historical data. Taking the prediction data of 2011-2020 as reference, when the improving rates of human-machine interface, human-environment interface, human-human interface and individual factor can be doubled respectively, the growths of the human errors prevention levels are 3%, 0.3%, 1% and 4% in turn. If the current condition is maintained and in about 2020, the proportion of the accidents attribute to cockpit human errors within the accidents attribute to human factors in China civil aviation transport aircrafts will be reduced to 15%.