Abstract
Revolutionary growth in technology has changed the way humans interact with machines. This can be seen in every area, including air transport. For example, countries such as United States are planning to deploy NextGen technology in all fields of air transport. The main goals of NextGen are to enhance safety, performance and to reduce impacts on environment by combining new and existing technologies. Loss of Situation Awareness (SA) in pilots is one of the human factors that affects aviation safety. There has been a significant research on SA indicating that pilot’s perception error leading to loss of SA is a one of the major causes of accidents in aviation. However, there is no system in place to detect these errors. Monitoring visual attention is one of the best mechanisms to determine a pilot’s attention and hence perception of a situation. Therefore, this research implements computational models to detect pilot’s attentional behavior using ocular data during instrument flight scenario and to classify overall attention behavior during instrument flight scenarios.
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Kilingaru, K., Nedic, Z., Jain, L.C., Tweedale, J., Thatcher, S. (2021). Classification of Pilot Attentional Behavior Using Ocular Measures. In: Phillips-Wren, G., Esposito, A., Jain, L.C. (eds) Advances in Data Science: Methodologies and Applications. Intelligent Systems Reference Library, vol 189. Springer, Cham. https://doi.org/10.1007/978-3-030-51870-7_12
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DOI: https://doi.org/10.1007/978-3-030-51870-7_12
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