Evaluated 403 vehicle models from top 14 manufacturers

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Measuring Cognitive Distraction
in the Vehicle
Joel Cooper
Precision Driving Research
David Strayer
University of Utah
Trends and usage
Evaluated 403 vehicle models
from top 14 manufacturers
• 98.3% offered Bluetooth
pairing
• 89.8% screen in center stack
• 50.4% offered smartphone
application integration.
• 94.3% offered a USB port
Available functions
• Make Calls
• Send and received text
messages
• Send and receive emails
• Update social media
• Control radio, climate, gps,
etc.
The Driver Distraction Triad
Visual:
Eyes off the Road
High
Moderate
Low
Manual:
Hands off the Wheel
Cognitive:
Mind off the Drive
Trends and Questions
• The Apps are coming…
• Hands and eyes free is increasingly seen as the solution
to visual distraction
Generally speaking, the same task will be less dangerous if
it can be achieved via an auditory / vocal interactions rather
than visual / manual interactions. However…
Potential risk is momentary demand and exposure
Q: Are the potential risks of some auditory/vocal tasks
greater than others?
Overview of AAA Project
• Most comprehensive study undertaken on mental
workload
• Systematic analysis, 3 studies, 150 participants, 8
conditions
• Analysis of different sources of distraction
• Driving simulator
• Instrumented vehicle
• Develop taxonomy of cognitive mental workload
• Category 1 – Workload associated with Baseline Driving
• Category 5 – Workload associated with Highly Demanding
Secondary task
Sources of Cognitive Distraction
•
•
•
•
Baseline Driving
Listen to Radio
Audio Book
Passenger Conversation
•
•
•
•
Hands-free cell conversation
Hands-held cell conversation
Speech-to-Text task
Mental Math (OSPAN)
Evaluation Platforms
Measures
• Primary
• Secondary
• Physiological
• Subjective
Developing a Metric of Cognitive
Workload
• Problem: Measuring cognitive workload is notoriously
difficult
• Objective: Develop robust instrument of cognitive
distraction
• Older technologies (e.g., radio, cell phone, etc.)
• Newer technologies (e.g., speech-based in-vehicle
communication)
• Standardized rating system
• Similar to other rating systems (e.g., Richter, Saffir-Simpson, etc.)
where higher ratings are indicative of greater cognitive distraction
Video of Instrumented Vehicle
Brake Reaction Time
Scanning for Hazards at Intersections
NASA TLX – Mental Workload
Cognitive Workload Scale
What does this mean in terms
of risk?
Increases in mental workload led to:
• Reduced visual scanning for hazards
• Reduced brake response time
• Reduced attentional capacity (as
measured by the p300 ERP)
• Mental Workload
Distraction
• Mental Workload
Risk
What does this mean in terms
of risk?
From other research
However…
•
•
•
•
•
•
•
•
Inattentional blindness
Impaired judgment and
decision making
General reduction in
visual scanning
Reduced frequency of
lane changes
Reduced stopping at
intersections
•
Reduced fatigue
Reduced boredom
Improved lane
maintenance
Increased visual attention
toward forward roadway
Summary of Results
• Category 1: Baseline, Radio, Book
• Category 2: Conversations (HH, HF,
Passenger)
• Category 3: Text to Speech
• Category 5: Mental Math
Summary and Results
• Proceed with caution!
• Text-to-Speech systems may be more
mentally demanding than
conversations.
Low frequency/ high risk potentially
equal to high frequency/ low risk
Future Directions
• How does the quality of speech affect
workload?
• How do errors in understanding affect
workload?
• How does an actual system, such as
Siri, fit on the scale?
• Are structured interactions more/less
demanding than unstructured
interctions?
Thank You!
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