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

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MODELING THE AIR TRAFFIC CONTROL TASK
Like any profession, ATC personnel experience day-to-day variation in performance,
and there are natural variations between controllers. In order to study these differences,
mentioned in most of the studies detailed above, a model needs to be built of the
controller, the environment, and the task, with the goal of locating where the majority
of changes may be occurring, and where any augmentation may be best suited to assist
in performance.
Specific to the air traffic controllers, the major variation source found when studying
large variations in performance was disruption of the circadian rhythm leading to a
disequilibrium condition described as a biological instability. Fortunately, no fancy
technology system was required to solve this particular problem, just proper human
resource management to avoid frequent shift switching. 35
Loft proposed that modeling the ATC task complexity and workload is insufficient to
predict performance due to the overriding effect of operator decision strategy. ATC
operators can select priorities, manage their own cognitive resources, and thus regulate
their own performance. The primary relief for the ATC operator is handing off traffic to
another local operator. 36 Our overall topic is concerned with a single pilot in a space
environment, where no room full of colleagues exists to take up the slack; therefore,
such group modeling techniques are outside the scope of the current treatise.
We do note that Loft develops excellent single-task descriptions of time pressure,
conflict detection, conflict resolution, etc.
As shown multiple times in the preceding section, single-task processing time and
intensity (difficulty or complexity) are the primary drivers of workload. Developing a
model connecting time, intensity, and effort, Hendy shows how decision time connects
a time-intensity-effort loop (Figure 5). Hendy contends decision time is the single
variable dominant in workload. Within this loop model, increasing the event rate is akin
to increasing task difficulty. The adaptation strategies are developed with training and
experience, a possible explanation of the difference in junior and senior performance
with augmentation aids.
Averty contends that ATC workload cannot be directly measured, but must be inferred
from a quantifiable mixture of including objective and subjective measures. He breaks
down the controller task into monitoring, vectoring, and conflict solving, and develops a
refinement of the NASA-TLX called TU. Averty's Traffic Load Index is based on number
of aircraft, but each aircraft is given additional weight according to processing
requirements on the controller, including both cognitive and emotional weight: for
example, aircraft with path conflicts to resolve are given the highest weight, while
isolated flyover traffic is given low weight. The authors conclude that TU needs to
include physiological inputs as well to fully model the task-controller interaction.
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