The role of Pilots' monitoring strategies in flight performance

Since decades, the number of aircraft accidents is continuously decreasing thanks to support systems and the introduction of automation. However, a drawback of this trend is that crews tend to be “automation addict” due to pressure and fatigue, which mean that they practice less and less manual flying. Also, an over-confidence in the automation can promote the occurrence of a particularly prominent typology of error: the failure of the crew to properly monitor the flight instruments, which can be particularly hazardous during the final approach phase. This paper describes an experiment that was undertaken to study pilot’s monitoring strategies thanks to eye tracking technology during manual approaches. We examined the relationship between visual patterns and flight performance (to find out if the approach was stabilized or not). The results show that gaze allocation of pilots who failed to stabilize their approach was sub-optimal. An analysis of the visual dispersion shows that they did not divide efficiently their visual attention compared to reference crew. Also, these pilots did not sufficiently gaze primary flight instruments requested to fly the approach (the attitude indicator, the localizer and the glide deviation scales). We assume that eye tracking may be a useful tool to improve pilots' monitoring strategies, for example gaze-training based on video clip showing experts’ visual pattern could help novice pilots to adopt appropriate gaze strategies

Predicting Inattentional Blindness with Pupillary Response in a Simulated Flight Task

Inattentional blindness (IB) is the failure of observers to notice the presence of a clearly viewable but unexpected visual event when attentional resources are diverted elsewhere. Knowing when an operator is unable to respond or detect an unexpected event may help improve safety during task performance. Unfortunately, it is difficult to predict when such failures might occur. The current study was a secondary data analysis of data collected in the Human and Autonomous Vehicle Systems Laboratory at NASA Langley Research Center. Specifically, 60 subjects (29 male, with normal or corrected-to-normal vision, mean age of 34.5 years (SD = 13.3) were randomly assigned to one of three automation conditions (full automation, partial automation, and full manual) and took part in a simulated flight landing task. The dependent variable was the detection/non-detection of an IB occurrence (a truck on the landing runway). Scores on the NASA-TLX workload rating scale varied significantly by automation condition. The full automation condition reported the lowest subjective task load followed by partial automation and then manual condition. IB detection varied significantly across automation condition. The moderate workload condition of partial automation exhibited the lowest likelihood of IB occurrence. The low workload full automation condition did not differ significantly from the manual condition. Subjects who reported higher task demand had increased pupil dilation and subjects with larger pupil dilation were more likely to detect the runway incursion. These results show eye tracking may be used to identify periods of reduced unexpected visual stimulus detection for possible real-time IB mitigation

Operating Different Displays in Military Fast Jets Using Eye Gaze Tracker

This paper investigated the use of an eye-gaze-controlled interface in a military aviation environment. We set up a flight simulator and used the gaze-controlled interface in three different configurations of displays (head down, head up, and head mounted) for military fast jets. Our studies found that the gaze-controlled interface statistically significantly increased the speed of interaction for secondary mission control tasks compared to touchscreen- and joystick-based target designation system. Finally, we tested a gaze-controlled system inside an aircraft both on the ground and in different phases of flight with military pilots. Results showed that they could undertake representative pointing and selection tasks in less than two seconds, on average