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Smart evaluation of instrument scan pattern using state transition model during flight simulator training
conference contribution
posted on 2019-05-10, 00:00 authored by K Kilingaru, Z Nedic, J Tweedale, Steven ThatcherTrainee pilots are expected to be thoroughly trained on both technical and nontechnical skills. Technical skills are relatively easy to evaluate. However, non-technical skills are hard to monitor and assess. This study investigates the feasibility of providing a smart evaluation technique that can generate feedback on trainee pilots’ instrument scan behavior. The authors conducted gaze monitoring experiments with a number of trainee pilots while operating a flight simulator in order to isolate patterns of behavior associated with Situation Awareness (SA). Recorded data on eye movements are then processed and transitions are extracted using a state transition model. The sequence of transitions are then processed to retrieve repeated instrument scan pattern. The results are verified using chart visualizations. © Springer International Publishing AG 2018.