Principal Investigators: Thomas Seacrist, MBE & Elizabeth Walshe, PhD, Children's Hospital of Philadelphia
Recognition errors – such as distraction, inadequate surveillance, and inattention – continue to be the leading cause of crashes among young drivers. These errors are largely attributable to limited capacity frontal-lobe cognitive abilities, some of which are still maturing through adolescence and into adulthood. This study builds upon prior CChIPS work utilizing millisecond-sensitive neuroimaging methods – magnetoencephalography (MEG) – and aims to:
- identify eye-tracking metrics that track MEG-recorded frontal lobe responses for cognitive control/demand during an established braking task;
- identify eye-tracking metrics that proxy increased cognitive control on a more cognitively challenging lead car braking task;
- compare these eye-tracking metrics and frontal lobe responses between healthy teens and teens with impaired cognitive control, specifically teens with autism spectrum disorder.
WHAT WAS THE PURPOSE OF THIS PROJECT?
Prior CChIPS work demonstrated we could detect cognitive control responses while driving among adults, typically developing teens, and atypically developing teens using our MEG+Driving+Eye-Tracking protocol. For this study, we wanted to advance this line of work by studying a more cognitively challenging task than the basic braking task already tested.
WHAT METHODS DID YOU USE?
We developed and added the more complex lead car-following task to the MEG+Driving+Eye-Tracking protocol, where the driver must follow a lead car at varying speeds, around curves, and in traffic and be prepared to brake at any time. Eye-tracking metrics were computed for periods of cognitive control (braking) and little to no cognitive control (coasting) and compared across the test sample of typically developing teens and teens with autism spectrum disorder (ASD).
WHAT DID YOU FIND?
We detected differences in saccade (a rapid movement of the eye between fixation points) distance and velocity, as well as blink rate (frequency of blinks per minute) between periods of coasting and braking in both typically developing teens and teens with ASD. The eye-tracking behaviors of the teens with ASD, however, suggested a higher cognitive workload required to complete the simulated drives.
HOW ARE THESE RESULTS APPLICABLE TO INDUSTRY MEMBERS?
Our findings can be used to advance in-vehicle technology to help reduce driver errors and increase driver attention. With the cost of eye-tracking technology going down, it’s possible that adding this technology to cars will soon become mainstream. By targeting cognitive errors, especially in young drivers, eye-tracking has the potential to prevent crashes.
WHAT’S NEXT?
To help us better understand changes in cognitive control neural responses and associated eye behavior, in Year 3 of this project we plan to add the unanticipated steering task to the simulated drive, which involves quick decision-making and precise motor control. We’re also excited to collect more data in a larger sample.
The mean (±SE) saccade amplitude (distance traveled during a rapid movement of the eye between fixation points) exhibited by (left) typically developing adolescents compared to (right) adolescents with ASD over 20 repetitive trials during a lead car-following task.
Exemplar eye-tracking patterns for a typically developing teen (top) and an autistic teen (bottom) during the basic braking task. The blue lines represent saccades (a rapid movement of the eye between fixation points), and the green dots represent individual gaze points. The typically developing teen primarily focused on the road ahead and traffic lights when approaching an intersection. The autistic teen focused on the instrument panel and speed limit signs more than the typically developing teen.
Co-Investigator
William Gaetz, PhD, Children’s Hospital of Philadelphia
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