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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/ j POI\ OFFICIAL ttSl!! 8HLY Chapter 2: Measurement of Mental Workload There are three approaches to measuring mental workload in a subject performing a primary task. The first is subjective evaluation, either post-hoc self-report questionnaires concentrating on how "busy" one may have felt, or an experimental observation of activity. The second is performance measures, an objective evaluation of how well the subject completes the primary task, a secondary task, or an experimentally inserted reference task. The final approach is to record real-time physiological measures, with the assumption that increased workload increases anxiety and this will be exhibited by changes in the autonomic nervous system (ANS). SUBJECTIVE MEASUREMENTS Self-report measures are appealing because they get inside the mind that was performing the task. There is no absolute objective scale to measure one person's "fully occupied" from another person's view of the same state; however, through rating scales and self-drawn graphs, one can obtain an accurate picture of how perceived workload evolved during the experiment. Perceived workload is important because it is what needs to be maintained between a subjective minimum, where attention may wander, and a subjective maximum, where increased emotion may decrease performance capacity. The most frequently used standardized self-report tools are the NASA Task Load Index (NASA-TLX or just TLX) and the Subjective Workload Assessment Technique (SWAT) .1,2,3.4 The TLX is a subjective workload assessment based on a multi dimensional rating questionnaire. An overall workload score is derived based on a weighted average of ratings on six subscales: mental demands, physical demands, temporal demands, own performance, effort, and frustration. SWAT is a two-step assessment of three workload factors: time load, mental effort load, and psychological stress load. In t he first step, hypothetica l activities are ra nked according to perceived workload. In the second step, the experimental task is eva luated post-hoc, using a 1-3 rating scale for each of the three dimensions. An interval scale of workload is derived, from 0-100, based on the reference data collected for each subject in the first step, and the evaluation of t he experimental task. A custom self-report can also be designed by the experimenter to specifically focus on the research questions in a given experiment. The second type of subjective measure is evaluation by an expert observer. In this type of measurement, assumptions are made on the mental activity of the subject based on the activities being performed. The advantage of th is approach is that there is minimal variance per-to-person if the same evaluator is employed. The disadvantage of this approach is the outside observer can miss workload mu ltiplyi ng factors such as task complexity contributing to an overwhelmed feeling by the subject. An example of this approach is the concept of utilization. In ca lculating utilization it is assumed that the subject must cognitively address one issue at a time in serial order. The measure of utilization is percent t ime busy, or addressing any issue, as opposed to waiting or monitoring for the next event. In general is it observed for control and supervisory tasks that at around 70% utilization performance begins to degrade. 5 Arguably not a perfect measure of workload, utilization has the advantage of simplicity, objectivity, UNCLASSIFIED/ /EOA OFFI&IAL l:ISI! er•t I 3
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Official release, from the pursue collection. The PDF is mirrored here; the original link is above. 31 pages are in the text index: search them above, or from the library's search.