This customer testimonial was created in collaboration with Georgia Tech and Smart Eye.

“My overarching goal is to ensure that technology is developed with the end user in mind. All aspects of a system or device’s design, implementation, adoption, and use can be enhanced by considering the perceptual, cognitive, and social needs and abilities of its users. At Georgia Tech’s Sonification Lab, we are looking forward to the next generation of product offerings that Smart Eye is rolling out, and I’m personally excited about the emotion capabilities, even more accurate gaze tracking (especially in eccentric views), and potential behavioral inferences and categorizations. I’m looking forward to collaborating with Smart Eye beyond data collection, but rather pushing the envelope to see what else we can collect and how to go about collecting it.”

— Prof. Bruce Walker, Lead at Georgia Tech Sonification Lab

Background

The Georgia Tech Sonification Lab is an interdisciplinary research group based in the School of Psychology and the School of Interactive Computing at Georgia Tech. Under the direction of Prof. Bruce Walker, the Sonification Lab focuses on the development and evaluation of auditory and multimodal interfaces, as well as the cognitive, psychophysical, and practical aspects of auditory displays, with particular attention to sonification. Special consideration is paid to Human Factors in the display of information in ”complex task environments,” such as the human-computer interfaces in cockpits, nuclear power plants, in-vehicle infotainment displays, and in the space program.

Georgia Tech had a recent interest in eye tracking for driving research – they wanted to know where people are looking in a dynamic way. When driving a car, people gaze all over the world outside of the vehicle – from traffic signs and the road to points far ahead of the vehicle to plan future maneuvers, or a novice driver looking close by. Driver gaze also varies inside the car.

For this study, they wanted to investigate how the design of the human-machine interface (HMI) in an automated vehicle can affect emotional responses such as excitement, perceived risk, psychological comfort, and even fear. Tracking where people look (for example, at the book they are reading, the HMI, or the roadway) along with pupil changes and other physiological metrics can tell researchers how people are reacting to the car’s behavior and the HMI messages.

The Solution

To achieve this, Georgia Tech needed an industrial research-grade eye-tracking solution. This means that the equipment, hardware, and even the data rate have to be suitable for research purposes. It needed to have the flexibility to push the boundaries of what it could do, including providing tech support and having people in the company who are willing to collaborate and explore.

Their requirements included understanding subject pupillometry – or the size of the pupil for all the various measures that it provides. They also needed a configurable and reconfigurable setup with multiple cameras that can be installed in a driving simulator, on a desktop, or around a kiosk, which allows for data collection in multiple situations. The Sonification Lab also needed an eye tracker that could be quickly calibrated, as well as good interaction with other data collection (HR, EEG, GSR, O2 Saturation, and more).

Smart Eye checked many of these boxes, and with the recent acquisitions of Affectiva and iMotions, they are beginning to check even more.

The Results

With Smart Eye, the Sonification Lab had the opportunity to collect a whole other channel of data beyond what can be collected in the driving simulator alone.

Most of the data that will be published will largely involve state-of-the-vehicle data, but by using eye tracking, they will be able to see what’s happening with the driver and correlate that with what is happening with the vehicle to get much more insightful research.

Using eye-tracking tools in their driving simulator, Georgia Tech researchers quantitatively demonstrated that a carefully designed HMI can have a major impact on passengers’ overall experience in an automated vehicle.

This eye-tracking technology allowed them to go beyond surveys and questionnaires and have a more systematic method for studying performance, preference, and emotional aspects of human-automation interaction in vehicles.

Looking towards the future, with Smart Eye’s recent acquisition of Affectiva’s Emotion AI capabilities, Georgia Tech is pursuing research on emotion using pupillometry, as well as behavioral categorization such as texting while driving, coffee in hand, and more.