The impact of alerting designs on air traffic controller’s eye movement patterns and situation awareness

Kearney, Peter; Li, Wen‐Chin; Yu, Chung-San; Braithwaite, Graham

doi:10.1080/00140139.2018.1493151

Cited by 23 publications

(6 citation statements)

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“…In this paper, the authors attempt to address some of the limitations found in mathematical models of the human pilot by using eye tracking data to provide insight into the way the pilot uses the available information. Although numerous studies have been carried out using eye-tracking for various purposes in aviation, for example recognising scan patterns of a remote air traffic control by a single controller [10], flight deck design [11], augmented reality (AR) in Primary Flight Display (PFD) [9], air traffic controller's situation awareness [7] and understanding human behaviour during aircraft-pilot coupling events [8], there has been limited transfer of this knowledge into the mathematical formulation of pilot behaviour. In this study the authors synchronise temporal and spatial eye-tracking data with aircraft data to study scenarios where the pilot is given an urgent safety critical task.…”

Section: Introductionmentioning

confidence: 99%

Understanding Human Behaviour in Flight Operation Using Eye-Tracking Technology

Korek

Mendez

Asad

et al. 2020

Engineering Psychology and Cognitive Ergonomics. Cognition and Design

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A clear understanding of how the pilot processes the information in the cockpit while carrying out particular tasks is crucial for developing the Human-Machine Interface and inceptors that help reduce pilot workload. Eye-tracking data synchronised with aircraft dynamics data is used here to study the high-workload scenario of executing an offset landing in an engineering flight simulator. The study focused on identifying differences in behavioural patterns between line pilots and test pilots. Evidence for significant differences were found regarding the ability to multitask and monitor aircraft states. The research output will lead to reduction of the pilot's workload and, in further study, proposition of a new display setups and inceptors.

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Section: Introductionmentioning

confidence: 99%

Understanding Human Behaviour in Flight Operation Using Eye-Tracking Technology

Korek

Mendez

Asad

et al. 2020

Engineering Psychology and Cognitive Ergonomics. Cognition and Design

Self Cite

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“…The number of blinks also reduced considerably with the increasing workload in both tasks. Pupil size is a reliable measure of workload (Beatty, 1982, Mandrick et al, 2016 as it dilates with increasing workload (Batmaz and Ozturk, 2008, Kosch et al, 2018, Truschzinski et al, 2018, Bernhardt et al, 2019, Kearney et al, 2019, Marinescu et al, 2018, Wanyan et al, 2014. Recarte et al, 2008 show that blink inhibition happens in higher workload conditions and so, the blink rate is inversely correlated with the attentional levels and workload experienced by the operator (Veltman and Gaillard, 1996, Brookings et al, 1996, Wilson, 2002, Borghini et al, 2014, Widyanti et al, 2017, Wanyan et al, 2018.…”

Section: Discussionmentioning

confidence: 99%

Unravelling the Physiological Correlates of Mental Workload Variations in Tracking and Collision Prediction Tasks: Implications for Air Traffic Controllers

Singh

Nguyen

et al. 2021

Preprint

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The surge in air traffic increases the workload experienced by air traffic controllers (ATC) while they organise traffic-flow and prevent conflicts between aircraft. Even though several factors influence the complexity of ATC tasks, keeping track of the aircraft and preventing collision are the most crucial. We have designed tracking and collision prediction tasks to elucidate the differences in the physiological response to the workload variations in these basic ATC tasks to untangle the impact of workload variations experienced by operators working in a complex ATC environment. Physiological measures, such as electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data, were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty. The mental workload in the tracking task was found to be positively correlated with the frontal theta power and negatively correlated with the occipital alpha power. In contrast, for the collision prediction task, the frontal theta, parietal theta, occipital delta, and theta power were positively correlated, and parietal alpha power was negatively correlated with the increases in mental workload. The pupil size, number of blinks and HRV metric, root mean square of successive difference (RMSSD), also varied significantly with the mental workload in both these tasks in a similar manner. Our findings indicate that variations in task load are sensitively reflected in physiological signals, such as EEG, eye activity and HRV, in these basic ATC-related tasks. Furthermore, the markedly distinct neurometrics of workload variations in the tracking and collision prediction tasks indicate that neurometrics can provide insights on the type of mental workload. These findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just 'when' but also 'what' to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in ATC and beyond.

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“…gether with electroencephalogram (EEG) [89], and a study of alerting designs to reduce ATCO response time to alerts [39]. Other applications include eye tracking for input to ATCO support tools [63] and for attention guidance [64].…”

Section: Sensing the Operator With Eye Trackingmentioning

confidence: 99%