Cue Utilization Predicts Resource Allocation during Rail Control Simulations: A NIRS Study

Abstract

This study was designed to examine whether cue utilization differentiates performance and resource allocation during simulated monitoring and process control tasks. The experiment involved the completion of a 45-minute rail control simulation that required participants to re-route trains either infrequently (monitoring task) or periodically (process control task). Implicit patterns of train movement were incorporated into the rail control task. Measures of participants’ response latency, fixation rates and cerebral blood flow were taken. Participants with higher cue utilization demonstrated greater decreases in fixation rates, smaller changes in cerebral oxygenation in the prefrontal cortex, and smaller increases in response latencies. The results provide support for the assertion that a relatively greater capacity for cue utilization is associated with the allocation of fewer cognitive resources during sustained attention tasks.

Get full access to this article

View all access options for this article.

References

Brouwers

Wiggins

M. W.

Griffin

Helton

W. S.

O’Hare

(2017). The role of cue utilisation in reducing the workload in a train control task. Ergonomics, 139, 1–16. https://doi.org/10.1080/00140139.2017.1330494

Brouwers

Wiggins

M. W.

Helton

O’Hare

Griffin

(2016). Cue utilization and cognitive load in novel task performance. Frontiers in Psychology, 7, 1–12. https://doi.org/10.3389/fpsyg.2016.00435

Brunswik

(1955). Representative Design and Probabilistic Theory in a Functional Psychology. Psychological Review, 62(3), 193–217. https://doi.org/10.1037/h0047470

Evans

D. C.

Fendley

(2017). A multi-measure approach for connecting cognitive workload and automation. Journal of Human Computer Studies, 97, 182–189. https://doi.org/10.1016/j.ijhcs.2016.05.008

Fallgatter

A. J.

Strik

W. K.

(1997). Right frontal activation during the continuous performance test assessed with near-infrared spectroscopy in healthy subjects. Neuroscience Letters, 223(2), 89–92.

Gould

J. D.

(1967). Pattern recognition and eye-movement parameters. Perception & Psychophysics, 2(9), 399–407.

Grier

R. a

Warm

J. S.

Dember

W. N.

Matthews

Galinsky

T. L.

Parasuraman

(2003). The vigilance decrement reflects limitations in effortful attention, not mindlessness. Human Factors, 45(3), 349–359. https://doi.org/10.1518/hfes.45.3.349.27253

Hancock

P. A.

Warm

J. S.

(2003). A Dynamic Model of Stress and Sustained Attention. Journal of Human Performance in Extreme Environments, 7(1), 519–537. https://doi.org/10.7771/2327-2937.1024

Helton

W. S.

Russell

P. N.

(2013). Visuospatial and verbal working memory load: effects on visuospatial vigilance. Experimental Brain Research, 224(3), 429–436. https://doi.org/10.1007/s00221-012-3322

10.

Helton

W. S.

Warm

J. S.

(2008). Signal salience and the mindlessness theory of vigilance. Acta Psychologica, 129(1), 18–25. https://doi.org/10.1016/j.actpsy.2008.04.002

11.

Helton

W. S.

Warm

J. S.

Tripp

L. D.

Matthews

Parasuraman

Hancock

P. A.

(2010). Author ’ s personal copy Neuropsychologia Cerebral lateralization of vigilance : A function of task difficulty Author ’ s personal copy, 48, 1683–1688. https://doi.org/10.1016/j.neuropsychologia.2010.02.014

12.

Kaber

D. B.

Endsley

M. R.

(1998). Team situation awareness for process control safety and performance. Process Safety Progress, 17(1), 43–48. https://doi.org/10.1002/prs.680170110

13.

Klein

G. a

Calderwood

Clinton-cirocco

(1986). Rapid decision making on the fire ground. In Proceedings of the Human Factors and Ergonomics Society annual meeting (Vol. 30, pp. 576–580).

14.

Langner

Eickhoff

S. B.

(2013). Sustaining attention to simple tasks: a meta-analytic review of the neural mechanisms of vigilant attention. Psychological Bulletin, 139(4), 870–900. https://doi.org/10.1037/a0030694

15.

Lansdale

Underwood

Davies

(2010). Something Overlooked? How experts in change detection use visual saliency. Applied Cognitive Psychology, 24(2), 213–225. https://doi.org/10.1002/acp.1552

16.

Loveday

Wiggins

M. W.

Searle

B. J.

(2013). Cue Utilization and Broad Indicators of Workplace Expertise. Journal of Cognitive Engineering and Decision Making, 8(1), 98–113. https://doi.org/10.1177/1555343413497019

17.

Molloy

Parasuraman

(1996). Monitoring an Automated System for a Single Failure: Vigilance and Task Complexity Effects. Human Factors: The Journal of the Human Factors and Ergonomics Society, 38(2), 311–322. https://doi.org/10.1177/001872089606380211

18.

Morrison

B. W.

Wiggins

M. W.

Bond

N. W.

Tyler

M. D.

(2013). Measuring Relative Cue Strength as a Means of Validating an Inventory of Expert Offender Profiling Cues. Journal of Cognitive Engineering and Decision Making, 7(2), 211–226. https://doi.org/10.1177/1555343412459192

19.

Pauley

O’Hare

Wiggins

M. W.

(2009). Measuring expertise in weather-related aeronautical risk perception: the validity of the Cochran–Weiss–Shanteau (CWS) Index. The International Journal of Aviation Psychology, 19(3), 201–216.

20.

Perry

N. C.

Wiggins

M. W.

Childs

Fogarty

(2012). Can reduced processing decision support interfaces improve the decision-making of less-experienced incident commanders? Decision Support Systems, 52(2), 497–504. https://doi.org/10.1016/j.dss.2011.10.010

21.

Poole

Ball

L. J.

(2006). Eye Tracking in HCI and Usability Research. Encyclopedia of Human Computer Interaction, 211–219.

22.

Reinerman-Jones

L. E.

Matthews

Langheim

L. K.

Warm

J. S.

(2011). Selection for vigilance assignments: a review and proposed new direction. Theoretical Issues in Ergonomics Science, 12(4), 273–296. https://doi.org/10.1080/14639221003622620

23.

Small

A. J.

Wiggins

M. W.

Loveday

(2014). Cue-based processing capacity, cognitive load and the completion of simulated short-duration vigilance tasks in power transmission control. Applied Cognitive Psychology, 28(4), 481–487. https://doi.org/10.1002/acp.3016

24.

Warm

J. S.

Matthews

Parasuraman

(2009). Cerebral Hemodynamics and Vigilance Performance. Military Psychology, 21, 75–100. https://doi.org/10.1080/08995600802554706

25.

Warm

J. S.

Parasuraman

Mathews

(2008). Vigilance requires hard mental work and is stressful. Human Factors, 50(3), 433–441. https://doi.org/10.1518/001872008X312152.

26.

Weiss

D. J.

Shanteau

(2003). Empirical assessment of expertise. Human Factors, 45(1), 104–116.

27.

Wickens

C. D.

(2002). Multiple resources and performance prediction. Theoretical Issues in Ergonomics Science, 3(2), 159–177. https://doi.org/10.1080/14639220210123806

28.

Wiggins

M. W.

(2011). Vigilance decrement during a simulated general aviation flight. Applied Cognitive Psychology, 25(2), 229–235.

29.

Wiggins

M. W.

(2014). Differences in situation assessments and prospective diagnoses of simulated weather radar returns amongst experienced pilots. International Journal of Industrial Ergonomics, 44(1), 18–23. https://doi.org/10.1016/j.ergon.2013.08.006

30.

Wiggins

M. W.

O’Hare

(1995). Expertise in Aeronautical Weather-Related Decision Making: A Cross-Sectional Analysis of General Aviation Pilots. Journal of Experimental Psychology: Applied, 1(4), 305–320. https://doi.org/10.1037/1076-898X.1.4.305

31.

Williams

A. M.

Ward

Knowles

J. M.

Smeeton

N. J.

(2002). Anticipation skill in a real-world task: Measurement, training, and transfer in tennis. Journal of Experimental Psychology: Applied, 8(4), 259–270. https://doi.org/10.1037/1076-898X.8.4.259