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Defense Intelligence Reference Document Cognitive Limits On Simultaneous Control Of Multiple Unmanned Spacecraft

Defense Intelligence Agency · 31 pages · text from the file's own layer

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.

  • p. 5 …time was necessary. The cognitive limitation of a human astronaut and his ability to perform the…
  • p. 6 …the fleet could be economically accomplished if only one remote pilot on station at a time…
  • p. 7 …At times of low demand the operator exerts effort to maintain vigilance (Al) until demand is…
  • p. 8 …The final approach is to record real-time physiological measures, with the assumption that increased workload…
  • p. 9 …time to an event stimulus is a typical real-time measure of speed. Outside the laboratory…
  • p. 10 …Detection of the R-wave allows measurement of frequency, time,d and amplitude. For continuous monitoring…
  • p. 11 …ET data will include position of a fixation and the time of each eye movement (or…
  • p. 12 …The difficulty lies in measurement time - typical fast assays of salivary cortisol still require about 15…
  • p. 13 …The FAA rebuilt the force to pre-strike levels during the rest of the 1980s. This…
  • p. 14 …existed in times immediately after peaks in workload. The second part of the study examined whether…
  • p. 16 …during the 8-hour workday, night time after work. Additionally, controllers completed the State- Trait Anxiety…
  • p. 18 …The authors conclude that psychophysiological data can be used to accurately measure workload in real-time…
  • p. 19 UNCLASSIFIED/ ,'1"1!11'- l!ll"l"ll!lllile lal!i! i;nn,~r The more…
  • p. 20 …As shown multiple times in the preceding section, single-task processing time and intensity (difficulty or…
  • p. 21 …Time pressure Time ~ Figure 5. Information Processing Model for a Human Operator. 37 In modeling the…
  • p. 22 …of the time, performance decreased due to decreased vigilance in confirming alarms properly on the ATC…
  • p. 23 …Results showed that the autoalert augmentation dramatically decreased the time to locate system failures, as well…
  • p. 25 …the time between the need for attention and the beginning of the next interaction time is…
  • p. 26 UNCLASSIFIED//509 OFFHiIJl1k W81!! 8HLY interfaces reduces the maximum number of aircraft controllable to seven. 51…
  • p. 27 …Whether it is the handwritten blocks for the ATCs, the stored instructions for the Dixon study…
  • p. 28 …We have shown the research progress in both areas, and the cognitive limits on the number…
  • p. 31 …A real-time traffic control scheme of multiple AGV systems for collision free minimum time motion…
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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
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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.