Experimental Studies of Cognitively Based Air Traffic Control Complexity Metrics for Future Operational Concepts
Author(s)
Hansman, R. John; Li, Lishuai
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New procedures and technologies of Air Traffic Control (ATC) under development in
Next Generation Air Transportation System (NextGen) will change controllers' tasks,
roles, and responsibilities. However, cognitive complexity will remain one of the limiting
factors in future system's capacity and none of existing complexity metrics can be
directly extended to evaluate cognitive complexity under future operational concepts.
Therefore, complexity metrics, applicable to future operational concepts, need to be
developed.
This thesis developed the structure for a cognitively based complexity metric,
Modified Aircraft Count (MAC). Cognitive complexity is decomposed based on
individual aircraft complexity factors and sector specific factors. The complexity
contribution of each aircraft is summed and adjusted by sector level complexity factors.
Cognitive principles, such as controller strategies, may be incorporated in aircraft specific
complexity factors and sector level complexity factors.
To investigate complexity factors in Modified Aircraft Count, two simulations were
developed to explore two proposed NextGen operational concepts, including Time-Based
Control at a Metering Fix and Dynamic Route Structure Control. Two experiments were
designed to evaluate controller performance and subjective workload under the simulated
operational concepts. The Time-Based Control at a Metering Fix was found to have
enhanced schedule conformance, reduced operational errors and lower perceived
complexity. The Dynamic Route Structure Control introduced longer hand-off acceptance
times, however, no other significant changes of controller performance and subjective
workload were found.
A new complexity probe technique was developed and applied in the two
experiments to explore individual aircraft complexity factors in Modified Aircraft Count.
In the new complexity probe, participants were asked to identify high complexity aircraft
from the screen shot of a traffic situation they had experienced. It was shown to be an
effective tool to assess aircraft specific complexity factors. Four complexity factors
(proximity to other aircraft, membership of a standard flow, proximity to weather, and
projected proximity to other aircraft) were examined by the relationship between their
corresponding observable factors and high complexity aircraft percentage. The chance of
an aircraft being considered as of high complexity increased if the aircraft was closer to
another aircraft, off the standard route structure, closer to the area impacted by weather,
or more likely to be in a conflict in the future.
Date issued
2009-09-09Series/Report no.
ICAT-2009-03;
Keywords
cognitive complexity, NextGen, Air Traffic Control, complexity, Modified Aircraft Count