Using Scanpaths as a Learning Method for a Conflict Detection Task of Multiple Target Tracking

Kang, Ziho; Landry, Steven J.

doi:10.1177/0018720814523066

Cited by 39 publications

(31 citation statements)

References 17 publications

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“…As a result, it was recommended that practice-based training be utilized over traditional frontal teaching methods when teaching nontechnical skills. Similarly, a study by Kang and Landry [18] explored using scanpaths as a learning method for air traffic conflict detection and showed significant performance increases and confidence boosts in students. A 2015 case study by Airservices Australia, detailed in [19], demonstrated the benefits of updated simulation systems with new features, such as recording, pausing, and replaying training sessions with both video and audio.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Air Traffic Control Training at the Federal Aviation Administration Academy

Updegrove

Jafer

2017

Aerospace

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This paper investigates current and future uses of simulation in the Federal Aviation Administration (FAA) Academy's Air Traffic Control (ATC) training program to identify potential improvement areas in the areas of simulation technologies and course content. Once identified, recommendations for changes to the current training program are made. A literature review of the current training techniques used at the FAA Academy and training centers was conducted. In addition, interviews were held and surveys were distributed to collect data regarding a variety of ATC training interest areas, such as virtual reality, current maintenance schedules, and simulator features. Finally, a cost-benefit analysis was conducted to determine the potential improvement areas with the highest feasibility for implementation and the highest potential to reduce training costs and/or time. The primary findings of this research revealed three feasible improvement areas to the current training process and simulation technologies: (1) reducing the dependence on instructors during simulation training, (2) utilizing web-based training methods, and (3) updating current simulator systems to include new features, such as recording and playback features. These changes were recommended to be implemented first, with voice recognition and virtual reality improvement areas being recommended as priority focus areas for future studies and/or implementation.

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Section: Literature Reviewmentioning

confidence: 99%

Optimization of Air Traffic Control Training at the Federal Aviation Administration Academy

Updegrove

Jafer

2017

Aerospace

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“…Analyzing visual scanning patterns and dynamic characteristics can help in understanding individuals’ underlying mental processes and scanning strategies; thus, these analyses can help in minimizing potential accidents and in designing appropriate human‐machine interfaces. To date, although there have been many visual scanning studies using dynamic glance measures (e.g., transitions of eye fixation) in aviation (Harris, Glover, & Spady, , Haslbeck & Zhang, , Kang & Landry, , Marchitto, Di Stasi, & Cañas, ), relatively few studies have explored drivers’ visual scanning patterns and dynamic characteristics. Underwood, Chapman, Brocklehurst, Underwood, and Crundall () identified driver's three scanning patterns (i.e., single/two/three‐fixation scanpaths) while driving on different road types (i.e., rural, suburban and dual‐carriageway).…”

Section: Introductionmentioning

confidence: 99%

Driver glance behaviors and scanning patterns: Applying static and dynamic glance measures to the analysis of curve driving with secondary tasks

Jeong

Kang

Liu

2019

Hum Ftrs & Erg Mfg Svc

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Performing secondary tasks (or non‐driving‐related tasks) while driving on curved roads may be risky and unsafe. The purpose of this study was to explore whether driving safety in situations involving curved roads and secondary tasks can be evaluated using multiple measures of eye movement. We adopted Markov‐based transition algorithms (i.e., transition/stationary probabilities, entropy) to quantify drivers’ dynamic eye movement patterns, in addition to typical static visual measures, such as frequency and duration of glances. The algorithms were evaluated with data from an experiment (Jeong & Liu, 2019) involving multiple road curvatures and stimulus‐response secondary task types. Drivers were more likely to scan only a few areas of interest with a long duration in sharper curves. Total head‐down glance time was longer in less sharp curves in the experiment, but the probability of head‐down glances was higher in sharper curves over the long run. The number of reliable transitions between areas of interest varied with the secondary task type. The visual scanning patterns for visually undemanding tasks were as random as those for visually demanding tasks. Markov‐based measures of dynamic eye movements provided insights to better understand drivers’ underlying mental processes and scanning strategies, compared with typical static measures. The presented methods and results can be useful for in‐vehicle systems design and for further analysis of visual scanning patterns in the transportation domain.

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“…Fourth, previous research in image analysis shows a strong connection between visual scan patterns and cognitive processing [21]. Some examples are found in radiology [54] - [56], chess [36] , [52], air traffic control [41]- [43] and reading [57] - [59]. In these activities, researchers found that although participants were asked to perform the same task, for example, playing chess, reading, or finding an abnormality in a chest X-ray, their visual scan patterns became more efficient as their level of experience increased [44].…”

Section: Visual Perception and Eye-trackingmentioning

confidence: 95%

“…Third, different eye-tracking studies in radiology [38], computer tomography [39], aircraft inspection [40], and in air traffic control [41] had shown that less experienced observers benefit from learning where expert observers looked when they performed their visual inspection task.…”

Section: Visual Perception and Eye-trackingmentioning

confidence: 99%

“…Similarly, expert chess players identified a chess-piece that was under attack faster than chess players with lower levels of experience [36], [52]. Air traffic controller research indicates that less experienced air traffic controllers perform a higher amount of visual computations and have less efficient visual scans [41]- [43]. Research on reading…”

Section: Visual Perception and Eye-trackingmentioning

confidence: 99%

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Identification of key visual areas that guide an assembly process in real and virtual environments

Rojas-Murillo¹

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Using Scanpaths as a Learning Method for a Conflict Detection Task of Multiple Target Tracking

Abstract: Implementing experts' scanpaths into novices' active learning process shows promise in enhancing training effectiveness and reducing training time.

Cited by 39 publications

References 17 publications

Optimization of Air Traffic Control Training at the Federal Aviation Administration Academy

Optimization of Air Traffic Control Training at the Federal Aviation Administration Academy

Driver glance behaviors and scanning patterns: Applying static and dynamic glance measures to the analysis of curve driving with secondary tasks

Identification of key visual areas that guide an assembly process in real and virtual environments

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