An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control
Due to increasing air traffic volume, current air traffic control (ATC) systems are reaching their maximum capacity. As such, there is a compelling need for a better ATC system and a ready batch of well-trained ATCOs. While it is important to expand the current pool of ATCOs to cope with the constan...
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sg-ntu-dr.10356-712092023-03-04T19:37:11Z An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control Lu, Patricia Chunqi Chen Chun-Hsien Khoo Li Pheng School of Mechanical and Aerospace Engineering Air Traffic Management Research Institute DRNTU::Engineering::Aeronautical engineering::Aviation Due to increasing air traffic volume, current air traffic control (ATC) systems are reaching their maximum capacity. As such, there is a compelling need for a better ATC system and a ready batch of well-trained ATCOs. While it is important to expand the current pool of ATCOs to cope with the constantly increasing air traffic demands, it is even more crucial to enhance their performance in the future ATC environment. In the first part of this study, the concepts of the Vertical Situation Display (VSD) aid, the Trajectory Prediction (TP) aid and the reliability of CRA were analysed to verify whether these information displays and CRA reliability would help reduce ATCOs’ workload and increase their Situational Awareness (SA). Results indicated that both the VSD and TP aid could significantly reduce ATCOs’ workload. Although there was no significant difference between VSD and TP, there was a trend of lower workload when ATCOs were equipped with VSD than with TP. Results also indicated that a reliable CRA could significantly reduce ATCOs’ workload and raise their SA. Although there was no significant difference between unreliable CRA and manual condition, there was a trend of higher SA when ATCOs were equipped with an unreliable CRA than without CRA. In the later part of this study, the author investigated the effects of the number of crossings, traffic flow and conflict situation on ATCOs’ physiological workload. The analysis of the Electroencephalogram (EEG) data obtained showed that only the number of crossings had a significant effect on ATCOs’ physiological workload. Yet, it was found that ATCOs’ physiological workload was slightly higher in 1:1 traffic flow than in 3:1 traffic flow condition though the difference was not significant. This study proved that equipping ATCOs with various aids could enhance their performance. Moreover, an understanding of the different factors that affect ATCOs’ workload and situational awareness allows new possibilities such as new information display designs and re-sectorisation to be explored. Bachelor of Engineering (Aerospace Engineering) 2017-05-15T07:40:33Z 2017-05-15T07:40:33Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/71209 en Nanyang Technological University 99 p. application/pdf |
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DRNTU::Engineering::Aeronautical engineering::Aviation Lu, Patricia Chunqi An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control |
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Due to increasing air traffic volume, current air traffic control (ATC) systems are reaching their maximum capacity. As such, there is a compelling need for a better ATC system and a ready batch of well-trained ATCOs. While it is important to expand the current pool of ATCOs to cope with the constantly increasing air traffic demands, it is even more crucial to enhance their performance in the future ATC environment. In the first part of this study, the concepts of the Vertical Situation Display (VSD) aid, the Trajectory Prediction (TP) aid and the reliability of CRA were analysed to verify whether these information displays and CRA reliability would help reduce ATCOs’ workload and increase their Situational Awareness (SA). Results indicated that both the VSD and TP aid could significantly reduce ATCOs’ workload. Although there was no significant difference between VSD and TP, there was a trend of lower workload when ATCOs were equipped with VSD than with TP. Results also indicated that a reliable CRA could significantly reduce ATCOs’ workload and raise their SA. Although there was no significant difference between unreliable CRA and manual condition, there was a trend of higher SA when ATCOs were equipped with an unreliable CRA than without CRA. In the later part of this study, the author investigated the effects of the number of crossings, traffic flow and conflict situation on ATCOs’ physiological workload. The analysis of the Electroencephalogram (EEG) data obtained showed that only the number of crossings had a significant effect on ATCOs’ physiological workload. Yet, it was found that ATCOs’ physiological workload was slightly higher in 1:1 traffic flow than in 3:1 traffic flow condition though the difference was not significant. This study proved that equipping ATCOs with various aids could enhance their performance. Moreover, an understanding of the different factors that affect ATCOs’ workload and situational awareness allows new possibilities such as new information display designs and re-sectorisation to be explored. |
author2 |
Chen Chun-Hsien |
author_facet |
Chen Chun-Hsien Lu, Patricia Chunqi |
format |
Final Year Project |
author |
Lu, Patricia Chunqi |
author_sort |
Lu, Patricia Chunqi |
title |
An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control |
title_short |
An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control |
title_full |
An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control |
title_fullStr |
An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control |
title_full_unstemmed |
An EEG-based empirical analysis of information display, situational awareness and workload in air traffic control |
title_sort |
eeg-based empirical analysis of information display, situational awareness and workload in air traffic control |
publishDate |
2017 |
url |
http://hdl.handle.net/10356/71209 |
_version_ |
1759858394980679680 |