Situation awareness model based on resource supply-demand difference and understanding

To further meet the development needs for human-machine interface of aviation equipment and to theoretically predict pilots’ situation awareness (SA) under the close combination of task with display and control interface design, this paper proposed a model for quantitative analysis of SA based on resource supply-demand difference and understanding. The model was based on the way the classical situation awareness rating technique (SART) scale defined SA, characterizing SA as the combination of resource supply-demand difference and understanding. The understanding was measured by multidimensional human-machine interface display format, while the resource supply-demand difference of task units was measured by combining task network analysis with multiple resource theory. To verify model validity, 30 subjects were selected to complete the simulated flight task in the airfield traffic pattern under different situation difficulties. The situation difficulty was adjusted by changing the simulated weather conditions, instrument display modes, and navigation map display modes. The SA was assessed under different situation difficulties by using subjective scales, flight performance, and eye movement indicators. The data analysis results show that the SA model results have good correlations with subjective (SART, crew awareness rating scale (CARS), and national aeronautics and space administration task load index (NASA-TLX) scales) and objective (manipulation performance, gaze entropy, and number of saccades) measurements. This preliminarily verifies the validity of the model. The proposed model can provide a theoretical basis and technical methods for the analysis and prediction of SA in combination with task flow design and display and control interface design features.