A Queueing Model of Visual Sampling Experimental Validation

Carbonell, Jaime R.; Ward, J; Senders, John W.

doi:10.1109/tmms.1968.300041

Cited by 79 publications

(33 citation statements)

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“…As such, this aspect of sequential task performance is often characterized by the term "task management" (Pattipati & Kleinman, 1991;Raby & Wickens, 1994;Meyer & Kieras, 1997;Chou, Madhavan, & Funk, 1996; see Wickens & Hollands, 2000 for a review of issues). Since foveal vision is often considered a restricted bottleneck, and the allocation of that vision to tasks is easily measured via scanning, visual scanning models have often been applied to understanding task scheduling in supervisory control environments, such as that encountered in the control of vehicles (Carbonnell, Ward, & Senders, 1968;Moray, 1986;Wickens, Helleberg, Goh, Xu, & Horrey, 2001). …”

Section: Theories Of Multiple Task Performancementioning

confidence: 99%

Workload Demands of Remotely Piloted Vehicle Supervision and Control: (1) Single Vehicle Performance

Wickens¹,

Dixon²

2002

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Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. Eighteen licensed pilots flew a remotely piloted vehicle (RPV) simulation on three 10-leg missions. The simulation required navigating to an enemy target, monitoring for unexpected targets in a 3D image display, and monitoring on-board systems. Both of the first two tasks required zooming in to inspect 3D images of the targets. Displays to support these activities were presented on a 19 inch Screen. Each pilot flew in a baseline condition, a condition supported by redistributing some information to the auditory modality, and a condition supported by automating much of the navigational tasks. The results revealed considerable interference between the tasks components. Some aspects of this interference were relieved by auditory offloading. However other aspects were not, suggesting that heavy cognitive demands of image manipulation dominated any benefit for using separate perceptual modalities. Navigational automation also relieved some aspects of task interference. The results are interpreted in terms of their relevance to different theories of multiple task interference, and to the concept of "cognitive tunneling".2

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Section: Theories Of Multiple Task Performancementioning

confidence: 99%

Workload Demands of Remotely Piloted Vehicle Supervision and Control: (1) Single Vehicle Performance

Wickens¹,

Dixon²

2002

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“…Carbonnell, Ward, and Senders (1968) found that this model predicted pilots' scanning behavior well in a flight simulator with experience pilots. A subsequent model of expected value, developed by Moray, Neil, and Brophy (1983) and Moray, Richards, and Low (1980), which used realistic experiments involving fighter aircraft, predicted with reasonable accuracy what proportion of time was spent fixating on the aircraft and other display features.…”

Section: Supervisory Monitoringmentioning

confidence: 77%

“…In a model of supervisory sampling, which integrates concepts from earlier models by Senders (1964), Carbonnell et al (1968, and Moray (1986), Wickens et al (2003) proposed four mediating factors that drive the allocation of visual attention: 1) Salience, 2) Effort, 3) Expectancy, and 4) Value. This SEEV model encapsulates findings from previous research and models described below.…”

Section: Supervisory Monitoringmentioning

confidence: 99%

“…For example, expertise will produce a more calibrated agreement between the operator's expectancy and importance (the mental model) and the true bandwidth and value of events. Moray (1986) notes that data from studies involving skilled pilots (e.g., Carbonnell, Ward, & Senders, 1968) show more optimal monitoring prescriptions than less skilled participants (e.g., Sheridan & Rouse, 1971), suggesting that training benefits performance in supervisory monitoring. Wickens et al (2003) also suggested that well-trained pilots allocate attention more optimally than their novice counterparts.…”

Section: Supervisory Monitoringmentioning

confidence: 99%

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Using Interference Models to Predict Performance in a Multiple-Task UAV Environment - 2 UAVs

Wickens¹,

Dixon²,

Chang³

2003

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“…This is not in and of itself a novel idea; the work domains may have changed, but the link between eye gaze and attention isn't new. Eye gaze has been theoretically linked to attention and cognition via the early foundational work in eye gaze measurement (Yarbus, 1967), other early work in instrument sampling in aviation (Carbonell et al, 1968), the 'spotlight' metaphor for eye gaze and attention (e.g., Posner et al, 1980), to more recent applications of eye gaze in reading (reviewed by Rayner, 1998), and general work regarding eye movements (Kowler, 2011). While the interest in eye gaze and the links to attention are not new topics, the capability to readily measure and record eye movements unobtrusively and in operation settings is a more recent capability that could be implemented for purposes of state assessment (Duchowski, 2002).…”

Section: Series 1 Seriesmentioning

confidence: 99%

Alternative Indices of Performance: An Exploration of Eye Gaze Metrics in a Visual Puzzle Task

Russell

2014

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Of interest to the U.S. Air Force is the ability to develop and characterize the level of workload that operators are under at any given point. When an operator's cognitive resources exceed demands, a 'red line' of performance may be crossed after which performance breaks down. What is needed is an estimate of operator state; a 'dipstick' for the operator in order to assess the level of 'resources' available, in order to avoid performance problems. Traditional approaches use secondary tasks (e.g., mental arithmetic) or secondary physiological measures (e.g., heart rate variability) for state assessment. However, the current work was motivated by dynamic systems theory which indicates that there are meaningful patterns of variability in 'primary' behaviors (e.g., required activities) which might provide a measure of operator state. The present work uses eye gaze as a primary measure in a visual puzzle task. The link between eye gaze and attention is generally accepted as is the link between attention and performance outcomes. The goal of Experiment 1 was to determine if performance changes in a visual puzzle task were reflected in eye gaze, as measured in multiple ways: conventional (e.g., average fixation length) & dynamic (e.g., β values, measures derived from a recurrence matrix). These relationships were explored in relation to task difficulty, time on task, as well as spare capacity. The results of Experiment 1 suggest that there are iii impacts of task demands on gaze patterns, for both conventional and dynamic gaze metrics. There were also significant of practice on eye gaze patterns in Experiment 1 that could be interpreted as learning or strategy shifts. The impact of learning on eye gaze was explored in a follow up experiment. The results of Experiment 2 show a significant improvement in performance in the task accompanied by change in gaze patterns when repeating the same puzzle; and that the dynamic measure of diagonal recurrence was systematically related to this performance change. This suggests that non-conventional measures of dynamic structure provide additional & complimentary information about operator state.

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A Queueing Model of Visual Sampling Experimental Validation

Cited by 79 publications

References 1 publication

Workload Demands of Remotely Piloted Vehicle Supervision and Control: (1) Single Vehicle Performance

Workload Demands of Remotely Piloted Vehicle Supervision and Control: (1) Single Vehicle Performance

Using Interference Models to Predict Performance in a Multiple-Task UAV Environment - 2 UAVs

Alternative Indices of Performance: An Exploration of Eye Gaze Metrics in a Visual Puzzle Task

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