Previous research has shown that the use of configural displays allows people to more easily detect changes in dynamic
processes for integration tasks thereby enhancing operator performance, yet the benefit of configural displays on
operator situation awareness (SA) has yet to be assessed. To test whether or not the use of configural displays impacts
the formation of pilot SA, a computer-based study was undertaken using two presentation rates (500ms and 1000ms)
and three configural display formats (Mil-Std-1787 HUD, Dual-articulated (DA) HUD, and the Arc Segment Attitude
Reference (ASAR)) to present aircraft flight reference information to pilots. One of five questions were possible
following the removal of the display from the screen, a query about aircraft airspeed, altitude, flight path angle (climb or
dive) or bank angle. The aim of the study was to demonstrate the ability to provide an increase in operator SA by
utilizing emergent features in configural displays to increase cue saliency and thereby increase operator SA. The
analysis of pilots' recall of aircraft flight path angle (percent correct) showed that pilots were significantly more aware
of aircraft attitude with the ASAR than with either the MIL-STD 1787 or DA HUD formats. There was no difference
among displays for recall of actual flight path angle (RMS error). The results are discussed in terms of the use of
configural displays as a design approach in representing task goals to facilitate operator SA.
To facilitate decision making tasks it is necessary to be able to "see" the situation. An enormous array of intelligence
gathering, database, and sensor sources of information are available. Methods for visualizing the information must be
established and information presented in such a way that human attention is captured and maintained on the most critical
aspects of the information. Visualizations need to adapt to the changing circumstances to show the most relevant
information at that time. We are developing a system called Holistic Analysis, Visualization, & Characterization
Assessment Tool (HAVCAT) that uses intelligent agents that interact with the user to provide the correct information at
the right time. This cutting edge system will enable visualization researchers to investigate techniques for adjusting
visualizations based on user performance HAVCAT will employ domain ontologies to determine relationships within
the data. The HAVCAT evidence reasoning agent distills the data and extracts the most pertinent actions or
consequences. This paper describes the HAVCAT concepts and also research issues related to development of
HAVCAT and techniques for directing user attention.
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