A Change in the Dark Room: The Effects of Human Factors and Cognitive Loading Issues for NextGen TRACON Air Traffic Controllers

  • Mark Miller
  • Sam HolleyEmail author
  • Bettina Mrusek
  • Linda Weiland
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 953)


By 2020 all aircraft in United States airspace must use ADS-B (Automatic Dependent Surveillance-Broadcast) Out. This is a key component of the Next Generation (NextGen) Air Transportation System, which marks the first time all aircraft will be tracked continuously using satellites instead of ground-based radar. Standard Terminal Automation Replacement System (STARS) in the Terminal Radar Approach Control (TRACON) is a primary NextGen upgrade where digitized automation/information surrounds STARS controllers while controlling aircraft. Applying the SHELL model, the authors analyze human factors changes affecting TRACON controllers from pre-STARS technology through NextGen technologies on performance. Results of an informal survey of STARS controllers assessed cognitive processing issues and indicates the greatest concern is with movements to view other displays and added time to re-engage STARS.


SHELL Human factors NextGen STARS TRACON Cognitive loading Distraction 


  1. 1.
    National Transportation Safety Board: 707 Fuel Exhaustion Avianca Flight 52 NTSB/AAR-04/91 (1991)Google Scholar
  2. 2.
    Hawkins, F.H.: Human Factors in Flight, 2nd edn. Ashgate, Aldershot (1987)Google Scholar
  3. 3.
    Miller, M.D.: Human factors computer information/automation beyond 2020 NextGen compliance: risk assessment matrix of situational awareness (cockpit computer use versus aviate, navigate, communicate). In: Presentation to FAA Aviation Safety Conference, Honolulu (2017)Google Scholar
  4. 4.
    Friedrich, M., Biermann, M., Gontar, P., Biella, M., Bengler, K.: The influence of task load on situation awareness and control strategy in the ATC tower environment. Cog. Technol. Work 20(2), 205–217 (2018)CrossRefGoogle Scholar
  5. 5.
    Pant, R., Taukari, A., Sharma, K.: Cognitive workload of air traffic controllers in area control center of Mumbai enroute airspace. J. Psychosocial Res. 7(2), 279 (2012)Google Scholar
  6. 6.
    Ravassard, P., Kees, A., Willers, B., Ho, D., Aharoni, D., Cushman, J., Aghajan, Z., Mehta, M.: Multisensory control of hippocampal spatiotemporal selectivity. Science 340(6138), 1342–1346 (2013)CrossRefGoogle Scholar
  7. 7.
    Neider, M., Zelinsky, G.: Cutting through the clutter: searching for targets in evolving complex scenes. J. Vision 11(14), 7 (2011)CrossRefGoogle Scholar
  8. 8.
    Corver, S.C., Aneziris, O.N.: The impact of controller support tools in enroute air traffic control on Cognitive error modes: a comparative analysis in two operational environments. Saf. Sci. 71, 2–15 (2015)CrossRefGoogle Scholar
  9. 9.
    Chang, Y., Yeh, C.: Human performance interfaces in air traffic control. Appl. Ergon. 41(1), 123–129 (2010)CrossRefGoogle Scholar
  10. 10.
    Federal Aviation Administration: Fact Sheet-Standard Terminal Automation Re-placement system. U.S. Dept. Transport, Washington (2016)Google Scholar
  11. 11.
    Li, W., Kearney, P., Braithwaite, G., Lin, J.: How much is too much on monitoring tasks? visual scan patterns of single air traffic controller performing multiple remote tower operations. Int.. J. Indust. Ergon. 67, 135–144 (2018)CrossRefGoogle Scholar
  12. 12.
    Giesbrecht, B., Sy, J., Bundesen, C., Kyllingsbæk, S.: A new perspective on the perceptual selectivity of attention under load. Ann. New York Acad. Sci. 1316(1), 71–86 (2014)CrossRefGoogle Scholar
  13. 13.
    Yin, S., Liu, L., Tan, J., Ding, C., Yao, D., Chen, A.: Attentional control underlies the perceptual load effect: evidence from voxel-wise degree centrality and resting-state functional connectivity. Neuroscience 362, 257–264 (2017)CrossRefGoogle Scholar
  14. 14.
    Greene, C.M., Soto, D.: Functional connectivity between ventral and dorsal frontoparietal networks underlies stimulus-driven and working memory-driven sources of visual distraction. Neuroimage 84, 290–298 (2014)CrossRefGoogle Scholar
  15. 15.
    Lind-Kyle, P.: Heal Your Mind: Rewire Your Brain. Energy Psychology Press, Santa Rosa (2010)Google Scholar
  16. 16.
    Koshino, H.: Effects of working memory contents and perceptual load on dis-tractor processing: when a response-related distractor is held in working memory. Acta Physiol. 172, 19–25 (2017)Google Scholar
  17. 17.
    Moacdieh, N., Sarter, N.: Display clutter: a review of definitions and measure-ment techniques. Hum. Factors 57(1), 61–100 (2015)CrossRefGoogle Scholar
  18. 18.
    Lohrenz, M., Trafton, J., Beck, M., Gendron, M.: A model of clutter for complex, multivariate geospatial displays. Hum. Factors 51, 90–101 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Mark Miller
    • 1
  • Sam Holley
    • 1
    Email author
  • Bettina Mrusek
    • 1
  • Linda Weiland
    • 1
  1. 1.Embry-Riddle Aeronautical University Worldwide College of AeronauticsDaytona BeachUSA

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