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This Defense Intelligence Reference Document, DIA-08-1101-001, is dated 15 December 2010. The Defense Intelligence Agency's Defense Warning Office produced it under the Advanced Aerospace Weapons System Applications program. It asks how many unmanned spacecraft one pilot could control in a future deep-space fleet, drawing on air traffic control and multiple unmanned vehicle research. It concludes the limits are about 16 craft for simple tasks, 7 for moderately complex ones and 4 for complex heterogeneous craft. It adds that physiological measures can signal operator overload.
From the source: Release of 2026-09-18 Incident: 12/15/10, Las Vegas, Nevada. Released with redactions. This document is a Defense Intelligence Reference Document (DIRD), a technical reference format used by the Defense Intelligence Agency (DIA) to capture baseline knowledge on a specific topic for later analytic use. DIRDs are best understood as reference and synthesis products rather than as original research. It is one of 38 DIRDs produced under the Advanced Aerospace Weapon System Applications Program (AAWSAP) between 2009 and 2011. Because AAWSAP’s scope permitted a broad range of supporting topics, not every DIRD in the series directly concerns aerospace systems or future threat assessment. The following summary reflects the DIRD’s scope and framing at the time of writing and should not be read as implying current validation of the concepts discussed. This DIRD examines how many unmanned spacecraft a single human operator could realistically supervise or control at once, using research from air traffic control and multi-vehicle remote piloting as rough analogs. The report argues that the practical limit depends heavily on task complexity: about 16 craft for simple monitoring or destination assignment, about 7 for moderately complex piloting or mission tasks, and about 4 for complex heterogeneous operations. It places particular emphasis on the operator’s ability to maintain a coherent mental “big picture” of multiple vehicles at once, and it suggests that automation and external displays can help by offloading working-memory demands, though not eliminating them. The document also highlights physiological workload measures as a possible way to detect or predict operator overload in real time. Overall, it presents multi-spacecraft control as a human-factors and systems-integration problem in which progress depends on managing cognitive limits through interface design, automation, and workload monitoring.
UNCLASSIFIED/ /FOR 8FFl@IAL li!H!! 8HL I crash any planes in any of the scenarios - this required approximately 6 hours of practice per participant before the experiment was conducted . Only one of the eight controllers in the Brookings study rated the overload condition as a loss of situational awareness. The resu lts compared the TLX, primary task performance, and physiological measures to low, medium, and high workload conditions, as well as the max or overload cond ition. Primary task performance is represented in Figure 4 (this chart was recreated visually from the source chart to accurately represent all trends), showing a trending effect for complexity but not volume. Additional results showed that changes in task difficulty (volume or complexity) produced changes in TLX, eye blink rate, respiration rate, and the EEG power spectra. The EEG power spectra were different for changes in volume versus changes in complexity. There were no observed significant correlations with heart rate or heart rate variability. The authors conclude that psychophysiological data can be used to accurately measure workload in real -time, an observation they note confirms earlier work on F4 crew members performing flight tasks of modulated complexity. 32 The Brookings data was reanalyzed by Wilson in 2003 using an artificial neural network approach as well as a stepwise discriminate analysis t o classify a physiological state as either operational or overloaded. Wilson successfully classified the overload condition consistently in more than 98% of the cases. The authors admit an issue with psychophysiological variation (day-to-day) that would need to be normalized and further research is required. 33 100 □ Volume ■ Complexity 80 □ Overload Ill -C ·o a. G) 60(J C ca E~ 0 -~ G) 40C. -C G) (J ~ G) C. 20 Low Medium High Max Workload Figure 4. Representation of Performance Results from Brookings Study. 30 Shown are the three scenarios with modulation of traffi c volume, complexity, and the overload condition . Note that the Low workload entry for the vol ume modulation performance (6 pla nes) was already 80% and this was sim il ar to the 12- pla ne medium complexity performance . Only the low complexity, 12-plane scenario showed near 100% primary task performance . UNCLASSIFIED/ JFOR OFFICIAL 091! er•tY 13
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