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 s Update social media Control radio, climate, gps, etc.

The Driver Distraction Triad Eyes off the Road Manual: Visual: Cognitive: High Low Moderate Hands off the Wheel 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? Mental Workload Distraction Mental Workload 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)

What does this mean in terms of risk? From other research Inattentional blindness Impaired judgment and decision making General reduction in visual scanning Reduced frequency of lane changes Reduced stopping at intersections However… 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!