Thesis Details
Pilot proficiency classification from gaze
This work deals with the classification of pilot proficiency level and basic flight maneuvers from gaze. The goal is to provide additional valuable tool for aviation instructors to evaluate proficiency of pilot students and provides them with feedback. This idea is based on results of numerous relevant studies, which discovered correlation between effective scanning patterns and domain performance. This thesis considers two proficiency levels~---~amateur and experienced. This work utilizes common analysis metrics of visual scanning and machine-learning classification techniques. The Support Vector Machine algorithm is used for the proficiency classification and Hidden Markov Models are utilized in basic flight maneuvers classification. The result of this thesis is a high accuracy proficiency classification and good ability to distinguish between individual basic flight maneuvers performed by pilots.
classification, machine-learning, supervised learning, Support Vector Machine, Hidden Markov Models, airplane piloting, pilot proficiency, scanning patterns, visual scanning, gaze-tracking, flight maneuvers
Beran Vítězslav, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Čadík Martin, doc. Ing., Ph.D. (DCGM FIT BUT), člen
Juránek Roman, Ing., Ph.D. (DCGM FIT BUT), člen
Křivka Zbyněk, Ing., Ph.D. (DIFS FIT BUT), člen
Milet Tomáš, Ing., Ph.D. (DCGM FIT BUT), člen
@mastersthesis{FITMT24569,
author = "Dominik Ruta",
type = "Master's thesis",
title = "Pilot proficiency classification from gaze",
school = "Brno University of Technology, Faculty of Information Technology",
year = 2022,
location = "Brno, CZ",
language = "english",
url = "https://www.fit.vut.cz/study/thesis/24569/"
}