Documents / Official release
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 FOR OFFICIJ!tt ttSI!! 8HLY Lee has previously shown that multiple automated ground vehicles can be autopiloted successfully in a two-stage process when nominal information is available beforehand about the environment to be searched. The two-stage process includes an offline, perm ission routing table generation where the primary path of each vehicle in planned and downloaded, and an on lin e traffic control stage where small changes to the plan are executed to avoid collisions and deal with contingent activity. 47 Attempting to increase the limits of UAV to pilot ratio, Ruff examined simulations using three augmented control techniques: manual, management by consent, and management by exception. The authors concluded that the middle level of automation performed best when considering that augmentation algorithms may have associated errors . They also concluded that the absolute maximum number of UAVs a person could control is four. Cummings addresses the UAV interface issue in a study on retargeting multiple in-flight cruise missiles. Cru ise missiles were chosen because they require minimal active piloting. A dual screen interface was constructed very similar to the ATC setup on one map and one list of objects being tracked (in the case of the ATC system, the li st is physica l rather than a second computer display - see Figure 3b). Cummings side -steps the issue of a cognitive workload metric based on complexity and number of tracked objects by assuming that an operator can execute changes to only one vehicle at a time, and then counting the ratio of time busy making changes to total time in a scenario. Th is measure is called utilization and previous work in systems engineering 48 and queuing theory has shown that utilization rates around 70% max out the typical human operator's ability to hold a big picture. We note that this scenario involves minimal interaction between the missiles, such as flight path conflicts. The missile study is compared to free flight ATC task, where en route and conflict resolution is the responsibility of pilots rather than ATC operators. Cummings develops several performance measures that are worthy, but for the current treatise an analogue is more succinct: the uti lization measure in multiple-object tracking and retargeting is similar to a grandmaster playing many games of chess simultaneously. They walk from board to board, think for a bit, make a move, and then move to the next board. Many high-level chess players can look at board position and evaluate what the next move is without knowledge of previous moves in the game. The question at hand is, how many simultaneous games can the grandmaster play before he is forced to revert to cold position analysis with every new presentation of a game? The conclusion is 16, and it agrees with previous work on free flight ATC. 49 Cummings additionally takes issue with the Ruff lim it of four UAVs, noting that this previous experiment included a far more demanding piloting task. More recent work by Cummings added aircraft heterogeneity to the experiment. 50 She concluded again that 70% utilization is optima l, but notes that the queu ing theory concept of wait times will sign ificantly affect the maximum number of vehicles that can be attended. In a multiple-vehicle control situation, a vehicle that has exhibited some decrement in performance has an interaction time with the operator to bring it back to acceptable performance. It will then follow its automated routine for a period, called the neglect time, until it falls again below performance threshold and requires the pilot's attention: the time between the need for attention and the beginn ing of the next interaction time is the wait time. Including wait times generated by more complex UNCLASSIFIED/ /FOR 0551Cl.t.k YSI!! fJNC I 20
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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.