A non-linear relationship between controller workload and traffic count

Lee, Paul U.

doi:10.1037/e577362012-006

Cited by 6 publications

(23 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Linear, exponential, and S-curve (estimating a categorical jump) functions were modeled and tested to see which function provided the best fit to the observed data. The results showed that the S-curve function captured more of the variance more consistently across multiple sectors and participants, suggesting that controllers perceive workload increases categorically with respect to the traffic count [7]. This categorical perception of workload matches well with a general phenomenon that controllers often report a low to moderate level of workload for seemingly busy traffic but report much higher workload with a few added tasks and/or minor off-nominal events once a certain traffic level is reached.…”

Section: Introductionsupporting

confidence: 62%

“…Given such a large variability, it would not be prudent to consider workload ratings as raw indicators of the maximum traffic that an "average" controller can handle since that number would vary significantly per controller. However, a key advantage of the S-curve functions was that they modeled the data more consistently across different individuals [7], suggesting that S-curve functions best capture the underlying cognitive perception of perceived workload.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Examining the Moderating Effect of Workload on Controller Task Distribution

Lee

Mercer

Callantine

2007

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Efforts to characterize controller workload -a key factor in limiting en route capacity -have produced mixed results. Subjective workload ratings reveal significant variations in minimum/maximum workload across individuals and show a categorical jump in perceived workload with a linear increase in aircraft count, making it difficult to predict workload limits with increased traffic. In addition, workload seems to be actively moderated by the controller to reduce monitoring tasks during high traffic/workload situations. In this paper, we examine this strategy shift by associating bookkeeping tasks and route/altitude clearances with online workload ratings. Overall, the data suggest that the controllers shed peripheral tasks related to monitoring and bookkeeping as the traffic ramps up and their perceived workload transitions from low to high. Whenever workload reached a maximum, some bookkeeping tasks were delayed and performed in "groups" after the peak traffic subsided.

show abstract

Section: Introductionsupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Examining the Moderating Effect of Workload on Controller Task Distribution

Lee

Mercer

Callantine

2007

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, Lee (2005) argued that the relationship between aircraft count ranging from 6 to 26 and workload was nonlinear. His participant controllers rated their workload while controlling air traffic.…”

mentioning

confidence: 99%

The Effect of Air Traffic Increase on Controller Workload

Hah

Willems

Phillips

2006

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

The Federal Aviation Administration (FAA) has been increasing the National Airspace System (NAS) capacity to accommodate the predicted rapid growth of air traffic. One method to increase the capacity is reducing air traffic controller workload so that they can handle more air traffic. It is crucial to measure the impact of the increasing future air traffic on controller workload. Our experimental data show a linear relationship between the number of aircraft in the en route center sector and controllers' perceived workload. Based on the extensive range of aircraft count from 14 to 38 in the experiment, we can predict en route center controllers working as a team of Radar and Data controllers with the automation tools available in the our experiment could handle up to about 28 aircraft. This is 33% more than the 21 aircraft that en route center controllers typically handle in a busy sector. * Now with Cleveland Air Route Traffic Control Center (ARTCC).

show abstract

“…Data from the aviation industry suggest that while routine aircraft traffic increases linearly, the air-traffic controller workload lurches from low to high at different air traffic thresholds, resulting in nonlinear increases in workload. 12 In such a complex, uncertain, and overwhelmingly nonlinear system as the labor and delivery unit, it is prudent to avoid planning workforce allocations using a reductionist approach based on average activity measures, 13 particularly when these reflect only a portion of the work involved.…”

mentioning

confidence: 99%