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This Defense Intelligence Reference Document, dated 15 December 2010, is a Defense Intelligence Agency report from its Advanced Aerospace Weapons System Applications (AAWSA) Program. It looks at how many unmanned spacecraft one human pilot could control during future deep-space missions, drawing on research into air traffic control and piloting of multiple unmanned vehicles. It concludes that the limits are about 16 craft for simple tasks, 7 for moderately complex tasks and 4 for complex mixed fleets. It adds that physiological measures can signal when an operator is overloaded.
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UNCLASSIFIED/ ,'1"1!11'- l!ll"l"ll!lllile lal!i! i;nn,~r The more recent Collet study recorded 5 ANS variables from 25 participants during real ATC operations. The population, mean age of 44, included only fully qualified operators, who were monitored for one hour during TRACON duty at Saint Exupery International Airport (Lyon, France). Correlation analyses were performed with the number of aircraft the operator was currently controlling. No adjustment was made for task complexity; however, data were acquired between 6 and 9 PM local time to collect medium and high workload data. Each participant handled between 1 and 10 aircraft during the study. The results of the correlation analysis are shown in Table 2. The authors conclude that changing the number of aircraft for professional ATCs produced correlations in physiological measures for SC, SBF, and IHR. 31 Table 2. Correlations among Physiological Variables in a study of air traffic controller workload modulation with variable number of aircraft. NA: number of aircraft; TLX: NASA self-report workload metric; Std SC: normalized skin conductance; Std SP: normalized skin potential; Std SBF: normalized capillary blood flow measured through the skin; Std ST: normalized skin temperature; Std IHR: normalized instantaneous heart rate. Bold values show significant correlation. SC, SBF, and IHR show significant correlation with changes in NA. Normalizations (standardizations) were performed against baseline data per subject to decrease inter-subject noise. 31 NA TLX Std SC Std SP Std SBF Std ST NA 1 TLX .98 1 p<.001 Std SC .93 .89 1 p=.002 p=.008 Std SP .77 .67 .91 1 NS NS p=.005 Std SBF -.97 -.94 -.87 -. 75 1 p<.0001 p=.001 P=.02 NS Std ST -.79 -.80 -.62 -.43 .82 1 NS NS NS NS NS Std IHR .98 .95 .97 .85 -.93 -.88 p<.0001 p<.0001 p<.0001 p=.03 p=.002 p=.005 Adaptive automation (AA) is the rebalancing of workload between the computer and human. Low workload levels can be supplemented with usually routine tasks that will keep the operator attentive, while providing the subject with additional mission information. This "extra information" may not be critical, but it will keep the subject from disengaging from the overall task. The goal of AA is to maintain peak performance of the system, in the Al to A3 regions. Kaber studied AA in terms of a simulated ATC task in 2005. Forty non-professional participants were monitored for primary and a probe secondary task performances. Results showed that primary task performance was greatest when AA was added to the system. 34 14 UNCLASSIFIED/ ,<EiOAt OEiEil&l11J.k leUiEii SU.bl/
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Report, from the dia collection. The PDF is mirrored here; the original link is under it. 31 pages are in the text index: search them above, or from the library's search.