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DESIGNING MULTIPLE UAV DISPLAYS
BASED ON THE HUMAN CAPACITY TO
PROCESS INFORMATION
PRESENTED BY:
Dr. William Marshak
Jeff S. Collier
SYTRONICS, Incorporated
Dayton OH
PRESENTED FOR:
Cognitive Engineering Research Institutes
Fourth Annual Human Factors of UAVs Workshop
Manning the Unmanned
21-24 May 2007
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Contents
Project Background
Human Cognitive Operating Characteristic
Multiple UCAV/UAV Cognitive Task Demands
Design Strategies
Voice Input/Output Using Context Agent Mediated Shallow Information Access
Temporal Mission Event Management
Distinguishing Plan from Hypothetical Replanning
Recognition Primed Decision-making (RPD) Display
Visual Thinking / External Cognition (VT/EC)
Summary
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Multiple UAV AGEncy (MAGE)
Tactical SituationSystem Display
Decision SupportSystem Display
Sandbox SystemDisplay
Purpose: Develop means
for integrating net-centricinformation to facilitate
multiple UCAV/UAV
control Employs intelligent agent
software and theory-baseddesign strategy
Transition to current
systems and systems in
development
Sponsor: Air ForceResearch Lab / Human
Effectiveness Directorate
(Dr. Mark Draper & Ms.
Gloria Calhoun)
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Human Cognitive Operating Characteristic
Perception bandwidth Vision-high, Audition-medium, Touch/Taste/Position-low Attention driven sampling from sensory stream Limited Short-Term Memory (STM) Capacity
(Miller's 72)
Large Long-Term Memory (LTM) Capacity (ifconsolidated)
Communication occurs within common cognitive
framework
Impedance matching between user and interfacefacilitates information flow Matching includes perception and cognitive (way we
think)
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Multiple UCAV/UAV Cognitive Task Demands
Vehicle states Internal status of propulsion,sensors, communications,etc.
Consumables status: fuel,power
Vehicle environment Flight characteristics, traffic
deconfliction Weather Threats
Mission demands Ground engagement
(surveillance, search,weapons strike)
Coordination (C3,Ground/JTAC, Intel, Air, ATC)
Lost Link
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Voice Input/Output with Context
Voice input using Nuance; speaker independent,
vocabulary limited system Switch actuated recognition made at any time
Voice output using Microsoft Speech SDK Text-To-Speech (TTS) speaks answers to queries
Context manager maintains elements of previous
conversation, filling in omissions in subsequent
queries Speech suitable responses delivered by TTS Non-verbal responses available in Decision Support
System Context correspondence maintained by selective
echoing Ubiquitous way people maintain context
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Agent Mediated Shallow Info Access
Information requirements driven
by both mission event andoperator
MAGE queries internal and net-centric sources to gatherneeded information
Most important information
loaded into workspace inexpandable window
Other information organizedunder tasks and accessible withone click
Avoids multi-layered menus
Reminds operator aboutrelevance
Operator queries supplementagent generated information
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Temporal Mission Event Management
One strategy for workload management isavoiding events from happening at the same time
Identifying time conflict among mission events
requires a temporal display Display includes time line for each vehicle, now
indicator, typed event strategy Automatic or manual scrolling through mission
time
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Distinguishing Mission from Hypothetical
Replanning
How to replan without losingawareness of the currentexecuting plan
Separate Tactical Situationand hypothetical Sandboxdisplays
Separates reality fromhypothetical, but allows side-by-side comparison
Includes spatial and time linerenditions of the mission plans
Tactical Display
Sandbox Display
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Recognition Primed Decision-Making
Display
Based on Klein (1989) observation experts
recognize what to do MAGE agency detects need for intervention Assembles a Decision Support Template to aid
and accelerate decision process
Instigation and decision alternatives presented Workspace allows recognition of the solution Shallow menu and voice query system make
more information available MAGE operator picks the most desirable
solution Enables better and faster decisions in high
workload environment
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Decision Support Template
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Visual Thinking / External Cognition (VT/EC)
Arnheim (1969) studies artists creative thinking and
postulates higher cognitive function evolved fromvision Visual representations consistent with visual processing
are easier to understand, mimic higher order reasoning Blink and RPD may be manifestations of Visual
Thinking
Examples include nomographs and DSTs Not only provide solutions, but reveal process of solution McKim (1972) proposes concrete principals governing
VT McEachren (1995) applies concept to maps Card, S. K., Mackinlay, J. D., and Shneiderman, B.
(1999) rediscover VT/EC Expand visual thinking to other senses broader term of
External Cognition
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Complex Judgements by Visual Thinking
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Evaluation of the VT Display
Brief study comparing bar graph representation of alternative
mission metrics with VT Widget (VTW) Observers taught criterion for judging 3 alternatives on 7
dimensions, including minimum acceptability Then judged sets of 12 trios of mission alternatives either in
a block of tables, bar graphs or in a block single VTWs
Choices were to rank three alternatives, detect if all threeviolate required minimums, and decision time recorded
Deviations from mathematical ideals, correct rejections of
minimum violations, and decision times were compared
between blocks in a dependent t-test
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Summary
Cognitive Systems Engineering of human cognitive
operating characteristic and system displays
reduces impedance and increases bandwidth This is accomplished by
Voice input/output with Context
Agent facilitated shallow information access Temporal mission event management Recognition primed decision-making aiding
display
Visual Thinking / External Cognition displays MAGE integrates net-centric feeds and multiple
vehicle control, overcoming much of the workload
overload