Classification of pilot attentional behavior using ocular measures

Kilingaru, K; Nedic, Z; Jain, LC; Tweedale, J; Thatcher, S

Classification of pilot attentional behavior using ocular measures

Kilingaru, K Nedic, Z Jain, LC Tweedale, J Thatcher, S

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Publisher:: Springer International Publishing
Publication Type:: Chapter
Citation:: Intelligent Systems Reference Library, 2021, 189, pp. 251-276
Issue Date:: 2021-01-01

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Field	Value	Language
dc.contributor.author	Kilingaru, K
dc.contributor.author	Nedic, Z
dc.contributor.author	Jain, LC
dc.contributor.author	Tweedale, J
dc.contributor.author	Thatcher, S
dc.date.accessioned	2022-05-17T00:30:39Z
dc.date.available	2022-05-17T00:30:39Z
dc.date.issued	2021-01-01
dc.identifier.citation	Intelligent Systems Reference Library, 2021, 189, pp. 251-276
dc.identifier.isbn	9783030518691
dc.identifier.uri	http://hdl.handle.net/10453/157437
dc.description.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.
dc.language	en
dc.publisher	Springer International Publishing
dc.relation.ispartof	Intelligent Systems Reference Library
dc.relation.isbasedon	10.1007/978-3-030-51870-7_12
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Classification of pilot attentional behavior using ocular measures
dc.type	Chapter
utslib.citation.volume	189
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2022-05-17T00:30:38Z
pubs.publication-status	Published
pubs.volume	189

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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http://hdl.handle.net/10453/157437