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The term automation generally refers to a machine capability to perform
functions normally attributed to humans. This research area considers,
more specifically, automation that assumes functions that control some
aspect of vehicle dynamics and/or operation of vehicle sub-systems. Of
critical interest is the well-established tendency for this form of
automation to not be robust, but instead limited to specific operating
conditions and types of operation, and to a small set of fixed behaviors
(i.e. modes). Because the automation cannot be proven to be safe in all
potential conditions, the human is typically left responsible for
supervising the automation and intervening in the event of any failure
or operation outside the ‘designed-for’ operating conditions. Thus, the
true robustness of automation can only be evaluated when the joint
automation-human system is considered collectively.
Research within the RAHS element applies methods, technology concepts,
and operator performance lessons-learned from Level 2 activities to
simultaneously design operating procedures and automated functions with
particular emphasis on robust automation-human performance. Solutions
posited and evaluated consider a range of possibilities from fully
automated to partially-automated to perhaps even fully manual methods of
flying aircraft along defined 4D paths. Systematic analysis establishes
a detailed definition of the flight deck automation functions necessary
for the NextGen operational environment. This analysis considers desired
automation functions, including those that may not be possible, or
practical, within current avionics architectures. A number of
operational environments may be considered as well, including, for
example, continuous descent arrivals, closely-spaced parallel approaches
and departures, metroplex operations, merging and spacing, and low
visibility arrivals and departures. These will be largely influenced by
close coordination with the ASP-Airspace and Airportal projects and
their ConOps developments.
Associate Principal Investigator: Sandy Lozito
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