Visual scanning strategies in the cockpit are modulated by pilots’ expertise: A flight simulator study

Abstract

During a flight, pilots must rigorously monitor their flight instruments since it is one of the critical activities that contribute to update their situation awareness. The monitoring is cognitively demanding, but is necessary for timely intervention in the event of a parameter deviation. Many studies have shown that a large part of commercial aviation accidents involved poor cockpit monitoring from the crew. Research in eye-tracking has developed numerous metrics to examine visual strategies in fields such as art viewing, sports, chess, reading, aviation, and space. In this article, we propose to use both basic and advanced eye metrics to study visual information acquisition, gaze dispersion, and gaze patterning among novices and pilots. The experiment involved a group of sixteen certified professional pilots and a group of sixteen novice during a manual landing task scenario performed in a flight simulator. The two groups landed three times with different levels of difficulty (manipulated via a double task paradigm). Compared to novices, professional pilots had a higher perceptual efficiency (more numerous and shorter dwells), a better distribution of attention, an ambient mode of visual attention, and more complex and elaborate visual scanning patterns. We classified pilot’s profiles (novices—experts) by machine learning based on Cosine KNN (K-Nearest Neighbors) using transition matrices. Several eye metrics were also sensitive to the landing difficulty. Our results can benefit the aviation domain by helping to assess the monitoring performance of the crews, improve initial and recurrent training and ultimately reduce incidents, and accidents due to human error.

Assessing expertise using eye tracking in a Virtual Reality flight simulation

“…For instance, aeronautical studies have shown that pilots' visual scanning strategies develop with level of expertise (Haslbeck et al, 2012;Haslbeck & Zhang, 2017;Yang et al, 2013;Ziv, 2016), and generally reflect a move towards shorter and more frequent fixations indicative of more rapid scanning of the instruments. Lounis et al, (2021) found shorter dwell times, and more complex transition sequences as indexed by entropy and Lempel-Ziv complexity. Consequently, as well as looking at the relationship between real-world expertise and simulator performance (i.e., construct validity), we aimed to assess whether real-world experts showed different gaze behaviours in the simulation.…”

“…Entropy, as a concept from information theory (Shannon, 1948), describes uncertainty about outcomes. When applied to eye tracking it indexes the level of randomness or variability in eye movements and has been previously used in assessing aviation performance (Allsop & Gray, 2014;Lounis et al, 2021;Vine et al, 2015) and can index whether a pilot is performing a structured and systematic scanning pattern, or a highly variable and inefficient one (Lounis et al, 2021). We adopted a simple measure of entropy described by Shannon and Weaver (1949), sometimes referred to as Gaze Transition Entropy (Lounis et al, 2021) which quantifies the complexity of the scan in 'bits', according to the formula:…”

Improving Airline Pilots’ Visual Scanning and Manual Flight Performance through Training on Skilled Eye Gaze Strategies

“…Effective cockpit monitoring is a key element of manual flight control. It helps to keep pilots in the loop by continuously updating their situational awareness about the current state of the aircraft [17]. Cockpit monitoring can be described as the methodical and meaningful visual scanning of instruments, necessary to control the aircraft trajectory or to make appropriate changes in aircraft attitude.…”

“…Visual scanning strategies (frequency and duration of fixations, visual scanning patterns, etc.) are greatly influenced by pilots' expertise, e.g., [17][18][19][20]. Gegenfurtner, Lehtinen, and Säljö [21] conducted a review of eye-tracking research in various fields such as radiology, driving, sport, and chess.…”

Situation Awareness Adaptive Alerting in an Aircraft Cockpit: A Simulator Study

“…In these contributions, different gaze metrics were proposed capturing the temporal, spatial and sequential dynamic of gaze behavior. With these measures, researchers were able to find differences between monitoring behavior of expert and novice pilots (Lounis et al, 2021) or identify poor monitoring as a reason for automation surprises (Sarter et al, 2007).…”