Poor cockpit monitoring has been identified as an important contributor to aviation accidents. Improving pilots’ monitoring strategies could therefore help to enhance flight safety. During two different sessions, we analyzed the flight performance and eye movements of professional airline pilots in a full-flight simulator. In a pre-training session, 20 pilots performed a manual approach scenario as pilot flying (PFs) and were classified into three groups according to their flight performance: unstabilized, standard, and most accurate. The unstabilized pilots either under- or over-focused various instruments. Their number of visual scanning patterns was lower than those of pilots who managed to stabilize their approach. The most accurate pilots showed a higher perceptual efficiency with shorter fixation times and more fixations on important primary flight instruments. Approximately 10 months later, fourteen pilots returned for a post-training session. They received a short training program and performed a similar manual approach as during the pre-training session. Seven of them, the experimental group, received individual feedback on their own performance and visual behavior (i.e., during the pre-training session) and a variety of data obtained from the most accurate pilots, including an eye-tracking video showing efficient visual scanning strategies from one of the most accurate pilots. The other seven, the control group, received general guidelines on cockpit monitoring. During the post-training session, the experimental group had better flight performance (compared to the control group), and its visual scanning strategies became more similar to those of the most accurate pilots. In summary, our results suggest that cockpit monitoring underlies manual flight performance and that it can be improved using a training program based mainly on exposure to eye movement examples from highly accurate pilots.
Improving Airline Pilots’ Visual Scanning and Manual Flight Performance through Training on Skilled Eye Gaze Strategies
2021
Article (Journal)
Electronic Resource
Unknown
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