Researchers from the University of Houston (UH) and the Texas A&M Transportation Institute (TTI) have produced an extensive dataset examining how drivers react to different types of distractions, as part of an effort to devise strategies for making driving safer.
The researchers have now made the full dataset publicly available for the first time in the Open Science Framework (OSF) databank, and described how they collected the information. The study was conducted with 68 volunteers, all of whom had a valid driver’s license and normal or corrected-to-normal vision, on a driving simulator.
Drivers were tracked with both thermal and visual cameras, along with palm and heart sensors, and an eye tracking system, which recorded perspiration, heart rate, breathing rate, gaze and facial expressions, to capture the drivers’ state as they were overloaded by multitasking.
Volunteers drove the same segment of highway four times in a high-fidelity simulator, with no distraction, and then with cognitive, emotional and physical distraction. At the same time, the simulator’s computer recorded driving performance variables including speed, acceleration, braking force, steering angle, and lane position. The study is the first to tackle three types of distracting elements: sensorimotor, such as texting; cognitive, such as absorbing thoughts; and emotional distractions.
The researchers found that texting led to far more dangerous driving, while a ‘sixth sense’ appeared to protect those suffering emotional upset or absent-mindedness. Texting interfered with that sixth sense, letting drivers drift out of their traffic lanes. Additional investigation showed that eye tracking and breathing rate proved useful metrics for measuring the impact of texting while driving, but that was not helpful in cases of emotional or cognitive distractions. However, the researchers found heart rate signals captured via wearable sensors, and perinasal perspiration captured via miniature thermal imagers, were able to track all forms of distraction.
“These and other findings provide the groundwork for future safety systems,” said Robert Wunderlich, director of the Center for Transportation Safety at TTI. “Given the widespread use of smart watches capable of measuring heart rate, this result opens the way for universal sensing of all forms of distraction at the consequential source, that is, the driver’s sympathetic system.”
Professor Ioannis Pavlidis, director of the Computational Physiology Lab at UH, said, “This experiment represents an emerging form of multimodal design, providing a 360° view of the studied conditions. These are now possible because of technological advances in wearable and imaging sensors, as well as the emergence of robust computational algorithms.”