New Insights for the Auto Industry: Identifying Key Eye-Tracking Metrics Associated with Cognitive Control While Driving, Validated by MEG Neuroimaging

Principal Investigator: Elizabeth Walshe, PhD, Children’s Hospital of Philadelphia

WHAT WAS THE PURPOSE OF THIS PROJECT?

Following our prior CChIPS project that integrated eye- tracking technology into our MEG+Driving+Eye-Tracking paradigm, we wanted to test the hypothesis that eye-tracking metrics are associated with increased cognitive control during simulated driving. As a first step, we aimed to establish the analytical pipeline for processing and analyzing the eye- tracking data we now are collecting and to see if we can detect differences in eye-tracking behaviors related to driving performance.

WHAT METHODS DID YOU USE?

We used custom-built driving scenarios that include driving tasks requiring different levels of cognitive control over behavior, paired with MEG neuroimaging, along with eye-tracking recording. We time-synced the MEG recording with the eye-tracking recording and used event markers in the driving scenario to align brain and eye responses with specific driving events (such as accelerating and braking in response to traffic light changes). We compared typically developing teens and teens with autistic spectrum disorder (ASD) in a small pilot-test sample.

WHAT DID YOU FIND?

This MEG+Driving+Eye-Tracking paradigm can detect differences in scanning behavior, even during a basic braking task. We observed three distinct eye-tracking behaviors: the “optimal driver” scans widely, the “sub-optimal driver” scans more centrally, and the “driver with ASD” is overattentive. (See graph.) The differences observed between periods of driving with cognitive control versus no cognitive control with the “optimal driver” suggests that eye-tracking could be used to measure cognitive control brain responses.

WHAT ARE THE INDUSTRY IMPLICATIONS?

Auto manufacturers may want to consider incorporating eye-tracking technology in their in-vehicle monitoring systems to measure cognition during driving, specifically for teen drivers.

WHAT’S NEXT?

We’re excited to collect more data in a larger sample and with a more challenging driving scenario to verify that these findings are consistent across individuals and groups (which is the goal of our CChIPS 2022-2023 project).

Fixations Chart — The mean (±SE) number of fixations (i.e., periods of time when the eyes are focused on an object of interest) exhibited by teen drivers over 20 repetitive trials during a basic intersection braking task. Drivers with ASD exhibited more fixations compared to “optimal” and “sub-optimal” typically-developing drivers, which is reflective of adolescents with ASD exhibiting “over-attention” to objects on the roadway (Ting Chee et al. 2019).

Co-Investigators

William Gaetz, PhD, Children’s Hospital of Philadelphia; Thomas Seacrist, MBE, Children’s Hospital of Philadelphia; Chelsea Ward McIntosh, MS, CCRP, Children’s Hospital of Philadelphia

Student

Emily Brown, Arcadia University

IAB Mentors

Dan Glaser, General Motors Holdings LLC; Suzanne Johansson, General Motors Holdings LLC; Susan Mostofizadeh, American Honda Motor Co., Inc.; Guy Nusholtz, Stellantis; Benjamin Austin, Toyota USA; John Lennenman, Toyota USA; Schuyler St. Lawrence, Toyota USA; Uwe Meissner, Technical Advisor