AAWSAP DIRD, Cognitive Limits on Simultaneous Control of Multiple Unmanned Spacecraft, December 2010

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/ /FAR AEEICl.'1.k W8f! er•tt
The enteric system executes control of smooth muscle. Although the CNS and PNS are
anatom ically distinct, they are functiona lly intertwined. When discussing the function of
the autonomic division, it is customary to refer to it as the Autonomic Nervous System,
or ANS .7
Changes in global arousal or activation through changing workload can result in
changes in physiological activity. These measures are advantageous as changes are
measurable continuously, in real-time, and usually unobtrusively in a naturalistic
setting. The drawback of using physiology alone is that there is no direct measure of
primary task performance.
Cardiac Function
Normal beating of the human heart produces a distinct and repeating pattern of
electrical activity measurable throughout the body for any two sample points that cross
the chest.c The typical electrocard iogram signal is shown in Figure 2.
R
Tp
Q
s
Figure 2. Typical EKG Signal for a Normal Heartbeat. Portions of the waveform are labeled P, Q,
R, S, and T.
Detection of the R-wave allows measurement of frequency, time,d and amplitude. For
continuous monitoring, heart rate measurements will vary considerably and in a non
linear fashion; therefore, the measurement of inter-beat-interval (IBI), the time
between R peaks, is more normally distributed in the absence of signal, reducing noise
in the measurement. 8 Averaging the heart rate over minutes of task performance and
comparing to baseline yields a reliable estimate of increased metabolic function. 9 An
additional measure is the heart rate variability (HRV), calculated by dividing the
standard deviation of IBI by an average value of IBI within a sample period. Additional
measurements can be made by decomposin g the spectra of HRV into low, mid, and
c In fact, a typical introductory physics course for life science students will include a laboratory experiment where
the heart rhythm is measured between electrodes located on the right wrist and left ankle.
d This time measurement is properly a phase measure ment, with the phase relative to some reference event.
UNCLASSIFIED/ /POI\ OfflelAL WS& €OIL¥
5