Distribution of Attention, Situation Awareness and Workload in a Passive Air Traffic Control Task: Implications for Operational Errors and Automation

Endsley, Mica R.; Rodgers, Mark D.

doi:10.2514/atcq.6.1.21

Cited by 69 publications

(43 citation statements)

References 3 publications

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“…It has been used in numerous domains including civil and military aviation, driving, nuclear, power plant control room operation and air traffic control and cited in previous studies, like [15][16] [17]. Its utilization has extended far beyond its original application of aviation and crew complement.…”

Section: Subjective Measuresmentioning

confidence: 99%

“…It has been used in numerous domains including civil and military aviation, driving, nuclear, power plant control room operation and air traffic control and cited in previous studies, like [15][17] [16]. It is "being used as a benchmark against which the efficacies of other measures, theories or models are judged" [18].…”

Section: National Aeronautics and Space Administration -Task Load Indexmentioning

confidence: 99%

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A theoretical framework for evaluating mental workload resources in human systems design for manufacturing operations

2018

International Journal of Industrial Ergonomics

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Manufacturing is a human-driven process that applies energy and manpower to produce consumer goods. In repetitive task processes like manufacturing systems, optimal performance is extremely important for the production employee and the company.In the general fast pace of manufacturing operations, there is the potential for operator errors, which correlates to possible safety issues and loss of revenue. This research explores the influence of cognitive resources on operator performance in manufacturing operations using the Multiple Resource Theory (MRT) and mental workload measures. Computer simulation models and mathematical modeling with Improved PerformanceResearch Integration Tool (IMPRINT) were used to assess mental workload resources to improve human system design for performance of the shop floor employee. This research presents the design, analysis and experimental implementation of a theoretical framework that provides a systematic approach for measuring mental workload using a combination of analytical and empirical techniques. Two experiments are presented to show the effectiveness of the proposed framework. As manufacturing operations become more complex, models can be used to provide recommendations for operator mental workload capacity planning. Therefore, this work is important to industry as manufacturing operations are changing by requiring more complex procedures, which increases the cognitive demand of the operator.iii

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Section: Subjective Measuresmentioning

confidence: 99%

“…It has been used in numerous domains including civil and military aviation, driving, nuclear, power plant control room operation and air traffic control and cited in previous studies, like [15][17] [16]. It is "being used as a benchmark against which the efficacies of other measures, theories or models are judged" [18].…”

Section: National Aeronautics and Space Administration -Task Load Indexmentioning

confidence: 99%

A theoretical framework for evaluating mental workload resources in human systems design for manufacturing operations

2018

International Journal of Industrial Ergonomics

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“…One hypothesis as to why air traffic control errors are made is that it is somehow due to "situational awareness" [8]. Performance on the recall task, which is often used as a measure of situational awareness, was generally poor.…”

Section: Discussionmentioning

confidence: 99%

“…Information such as aircraft type, call sign, and groundspeed, is recalled less than 40% of the time (see [6] and [8]). Information that is of more direct value to the controller's task, however, such as the position of aircraft, the initial alphabetic part of a call sign, and control level (whether the aircraft was in the sector, about to enter, etc.)…”

Section: Detecting Clusters By Recallmentioning

confidence: 99%

A methodology for studying cognitive groupings in a target-tracking task

Landry

Sheridan

Yufik³

2001

IEEE Trans. Intell. Transport. Syst.

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-Subjects performing visual target tracking tasks have been shown to utilize perceptual organization. This organization has both Gestalt and goal-oriented features. Previous studies have attempted to use memory recall techniques to examine potential cognitive groupings in air traffic control (ATC), which is, in part, a complex target tracking task. In the present research, a special form of cluster analysis was successful in revealing cognitive groupings having appreciable influence on task performance in a targettracking task designed to resemble ATC. The method of cluster analysis was derived from the "virtual associative network" model of memory organization, and applied to the record of eye fixations in the course of task performance. Results using inexperienced subjects showed fixation clustering consistent with Gestalt factors. Task objectives (such as conflict detection) did not seem to affect grouping as much. The subjects' recall was generally poor, except where direct manipulation of targets occurred. We conclude that a) cognitive grouping influences performance, b) recall techniques may not be able to elicit subjects' cognitive groupings, and c) such groupings can be determined via analysis of eye fixations. These findings have implications for studying workload assessment and information structuring in complex visual scanning tasks.

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“…Numerous empirical evidences confirm that ATCos may be poor in detecting aircraft-to-aircraft conflicts when they are not actively controlling the airspace but nevertheless have to monitor for occasional anomalies. As illustration, Endsley and Rodgers [13] found that ATCos showed poor performance in detecting conflicts in recorded traffic when they were passively monitoring the traffic. Galster et al [14] found that passive monitoring with airborne control of aircraft separation, which would be the case under mature Free Flight, led to a marked decrease in conflict detection performance by ATCos under high traffic load.…”

Section: Failure To Detect (Level 1)mentioning

confidence: 99%