Aircraft flying is a process that requires real-time monitoring of cockpit environment changes, continuous attention to surrounding environmental information, continuous filtering of irrelevant information and making correct decisions. Vision, as one of the most widely used sensory channels, plays a crucial role in the driving process. Pilots rely on the vision system to detect changes in the scene at all times. If they fail to detect changes in the cockpit during the flight process, there may be serious consequences. For example, on February 4, 2015, the captain of Flight 235 of TransAsia Airways in Taiwan, China, took the initiative to remove the autopilot in case of the failure of the second engine. In the process of manual pilot, due to the operating pressure of high load and his own tension, the captain appeared to be affected change blindness. Forty-three people died and 15 got injured when the captain ignored the co-pilot’s cross-check request and information of engine no. 2’s automatic shunting. This inability to detect significant stimulus changes is called change blindness. Change blindness usually involves two conditions: one is the failure to perceive a new stimulus, while the other is the failure to detect the changes of the original stimulus in the position and motion state.
In recent years, traffic accidents caused by change blindness remain high; hence scholars have carried out corresponding studies on change blindness in the field of traffic. Studies on the influencing factors of change blindness can be divided into two categories: scene change characteristics and driver characteristics. The characteristics of scene change can be further sub-divided into visual salience of change, security relevance of change, change position and scene complexity. In the field of road traffic, Galpin et al. found through experiments that drivers are more likely to be alert to driving-related information in complex traffic scenes, but find it difficult to detect sudden irrelevant changes. Beanland studied the difference in drivers' change detection of seven types of objects, including road signs, vehicles and pedestrians, in urban scenes and rural scenes, and categorised the safety correlation of the target objects. According to the results, drivers in rural areas showed more accurate and faster responses and were less affected by change blindness. In addition, the target of safety related to driving on the rural scene change detection have no obvious effect on performance, which is different in a city driving scene, where drivers prove to be more efficient in change detection of high security correlation targets. Beanland also reported that the visual significance of the change of the target affected the subjects’ efficiency of change detection, that is, the greater the difference of the change of the target before and after, the better the performance of the change detection of the subjects. In the experimental study of Zhao, with the centre of the screen as the origin, 25% of vertical and horizontal areas were defined as the centre area, and the rest as the edge area. The study results show that drivers perform better in scene change detection in the central area than in the edge area. In the field of civil aviation traffic, Mayo applied eye-movement tracking technology to study whether the upgrade of the Synthetic Vision Systems (SVS) display system would reduce the incidence of change blindness in subjects, but the results showed that the improvement of display technology did not improve the efficiency of change detection in pilots. Ahlstrom 's study showed that the complexity of information display in the SVS system increased the time of change detection and reduced the efficiency of change detection for pilots.
Driver characteristics can be divided into attention span and memory capacity, cognitive or psychological load, and level of driving experience. In the field of road traffic, Yanqun Yang et al. explored the effects of emotion induction and driving tasks on change blindness through experiments, and found that both positive and negative emotions led to varying degrees of decline in the drivers' change detection level, but negative emotions had a more significant impact. Filtness et al. studied the relationship between change blindness and drivers' sleepiness due to sleep deprivation, and found that sleepiness had no significant influence on the drivers' change detection level. Murphy 's study proved that when a driver is under a high load, his cognitive resources will be too occupied, leading to a decrease in the detection efficiency of the change of the target, thereby making them prone to change blindness. The experimental study of Crundall shows that drivers' ability to detect risk changes is correlated with their experience level. The richer the driving experience, the higher the detection efficiency of risk changes. Change awareness ability can be obtained through perception training. In the field of civil aviation traffic, Zarate explored the change detection efficiency of aircraft pilots for aircraft display by taking professional knowledge level and regional position as influencing factors. The results showed that there was no significant difference between expert pilots and novice pilots in their response to change detection. McDermott studied the visual search efficiency of pilots' experience level with the SVS display system, and found that pilots with low experience level perform better than those with high experience level in attention performance.
Based on the above analysis, it can be seen that current studies on the influencing factors of change blindness in civil aviation mainly focus on cockpit display and experience level. However, there are hardly any studies on the influencing factors and interaction of other control devices (such as knobs) that may cause change blindness. In addition, most of the above studies only take behavioral indicators or eye movement indicators as the measurement basis, and the occurrence of change blindness is largely due to behavioral and eye movement indicators . Therefore, this study carries out an experimental investigation, taking the position of the knob interface layout as the influencing factors, with the eye movement index and behavior index as the basis, to analyze the interaction between these factors, and provide guidance for pilots regarding change blindness in the process of human-computer interaction.