In order to investigate the effect of different multimodal redundant alarm design on the reaction performance of armored vehicle occupants under a noisy environment, 24 participants were recruited and subjected to simulation driving experiments utilizing a new type of high-fidelity armored vehicle semi physical simulation platform. Three alarm redundancies were tested: visual channel, auditory channel, and audio-visual dual channel designs, across high and low noise conditions. The findings demonstrate that, in comparison to the visual channel redundancies, drivers' response error rate and reaction time to warnings are substantially reduced in the auditory channel redundancies and audio-visual dual channel redundancies. The response error is generally lower in low noise environments than in high noise environments, although response time remains consistent across noise conditions. The interaction between noise conditions and alarm design does not significantly affect alarm response performance, eye movement indicators, or subjective workload scores. Comparing the multimodal alarm with redundant auditory prompts to the visual-only redundancy, the study finds that the former significantly enhances drivers' reaction to warning information. However, the combination of auditory and visual redundancy does not yield further performance improvements. A low noise environment positively influences response performance enhancement.

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.

Early Warning Aircraft (EWA) are the main force for air detection and its Human-Machine Interface (HMI) should be designed to support task efficiency and safety. With the application of advanced input method and interface design in EWA, little is known about their actual usability in terms of human factors and ergonomics. The aim of this study was to investigate the effects of the input method and display mode of the situation map on EWA reconnaissance task performance with different information complexities. Eighteen participants attended a three-factor within-subject design experiment with input method (touch screen and mouse), display mode of the situation map (color and grayscale), and information complexity (high and low) as the independent variables. Participant behavior performance, subjective workload, heart rate/heart rate variability, and eye movements were recorded as the dependent variables. The results suggest that a touch screen requires greater task completion time and has greater physical demands than mouse operation; however, it also facilitates information processing by reducing the average fixation time. Color mode significantly decreases saccade counts compared to grayscale mode and is considered more appropriate for target search tasks as it induces less visual search load. High information complexity produces significant negative effects on behavior performance and subjective workload. It also has significant interaction effects with input method on fixation and saccade counts. The findings have implications in the optimization design of Human–Machine Interface for EWA task systems.