Bracketing Human Performance to Support Automation for Workload Reduction: A Case Study

  • Robert E. WrayEmail author
  • Benjamin Bachelor
  • Randolph M. Jones
  • Charles Newton
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9183)


Semi-automated Forces (SAFs) are commonly used in training simulation. SAFs often require human intervention to ensure that appropriate, individual training opportunities are presented to trainees. We cast this situation as a supervisory control challenge and are developing automation designed to support human operators, reduce workload, and improve training outcomes. This paper summarizes a combined analytic and empirical verification study that identified specific situations in the overall space of possible scenarios where automation may be particularly helpful. By bracketing “high performance” and “low performance” conditions, this method illuminates salient points in the space of operational performance for future human-in-the-loop studies.


Simulation-based training Semi-automated forces Cognitive workload 



This work is supported by the Office of Naval Research project N00014-1-C-0170 Tactical Semi-Automated Forces for Live, Virtual, and Constructive Training (TACSAF). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Department of Defense or Office of Naval Research. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. We would like to thank collaborators and sponsors at NAWC TSD and ONR who have provided insights and operational perspectives in the development of TXA: LCDR Brent Olde, Ami Bolton, Melissa Walwanis, and Heather Priest.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Robert E. Wray
    • 1
    Email author
  • Benjamin Bachelor
    • 1
  • Randolph M. Jones
    • 1
  • Charles Newton
    • 1
  1. 1.Soar Technology, Inc.Ann ArborUSA

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