Given that more vehicles with autonomous features are becoming available to consumers, we are interested in looking into how autonomous functionality can be implemented without compromising motorists’ safety. How can we ensure that drivers are monitoring the road when they are using autonomous functionality? What is the best way to hand over control of the vehicle in situations where autonomous functionality fails? Are the interfaces designed for autonomous functions effectively communicating pertinent information to the driver? To examine these questions, we are equipped to use both simulated and on-road driving scenarios for testing. Currently, we are conducting an on-road study on the effects of autonomous driving on cognitive distraction and mind-wandering.
Basic Cognitive Performance
People make mistakes. Surgeons operate on the wrong body part, air traffic controllers assign the same runway to two different planes, and people continue to die in car crashes caused by human error every day. These types of errors have many similarities, such as dynamic environments with large amounts of perceptual information, time limits for critical decision-making, and the continuous maintenance of voluntary, goal-directed behavior. Psychologists have identified a significant predictor of the source of these errors: Cognitive Load. Cognitive load refers to the amount of mental effort, or workload, required to perform a task, and researchers quantify this effort with a combination of behavioral, physiological, and neurological measures. We seek to utilize these methods to provide converging evidence of the cognitive processes underlying psychological constructs, such as cognitive load and inattention blindness.
Center For Distracted Driving Research
Driver distraction is “the diversion of attention away from activities critical for safe driving toward a competing activity” (Strayer et al., 2017). According to 2015 CDC estimates, over 1000 people are injured and 9 people are killed daily in the United States from accidents that involve a distracted driver. Sources of distraction vary from outside objects, like cell phones, to built-in vehicle technologies, such as voice recognition systems, text messaging capabilities, and even web browsers. Our current aim is to examine the demand associated with using built in technologies while driving. So far, our findings suggest that much of the functionality in these vehicles is too demanding to safely use while driving. We are hoping the current project, commissioned by the AAA Foundation for Traffic Safety, will provide the information necessary for the auto industry, drivers, and public policy-makers alike to create the safest on-road experience possible.
Cognition In The Wild
Biophilia suggests all humans have an innate appreciation for nature. The theory of attention restoration states that spending time in natural environments can restore cognitive resources such as attention. Our lab aims to understand the underlying neural correlates of attention restoration through exposure to nature. Our research uses neuroimaging techniques such as electroencephalography (EEG) to determine changes in neurological responses from exposure to nature in correlation with changes in behavioral measurements and subjective reports. We hope to determine the underlying neural processes of restoration, as well as understand how restoration can be enhanced or induced to support nature-based therapies. More research is necessary to determine the neurological health consequences of spending time in nature.
In an effort to minimize visual and manual distractions in the vehicle, many automakers are experimenting with voice and audio interactions, as well as gesture commands for controlling in-vehicle systems. As with the unintended consequences of trading visual and manual distractions for cognitive distractions, gesture control may or may not alleviate the current distractions caused by existing systems. We aim to test these systems for their viability as a replacement for some of the current systems in the vehicle.
HMI and Useability Assessment
To assess the usability of various in-vehicle technologies, researchers of the Center for Distracted Driving Research utilize the theoretical framework of human-machine interaction (HMI). This framework typically applies to high-risk environments and task-critical interactions between an operator and a machine. The framework consists of many other established evaluation methods and techniques from applied psychological principles and human factors, as well as traditional industry and engineering assessments inspired by risk management. This lab aims to evaluate the myriad of in-vehicle technologies such as infotainment, voice command, and advanced driver-assistance systems (ADAS).
Over the last decade, the University of Utah has been studying driver distraction to better understand how and why people can become overloaded while multi-tasking. We use sophisticated equipment, including driving simulators, eye trackers, brain activity measurements, such as electroencephalography, and neuroimaging technology, such as functional magnetic resonance imaging, to understand the cognitive neuroscience of driver distraction. Several special populations have also been identified through benchmark tests. A very small percentage of the population fails to show decreased performance while multi-tasking. These individuals are referred to as “Supertaskers”. The Applied Cognition Lab is currently collecting a database of Supertaskers through the Gatekeeper task, which is hosted online at supertasker.org.
Dr. Strayer’s Center for Distracted Driving Research and Applied Cognition Lab are housed in the Department of Psychology within the College of Social and Behavioral Sciences Building (BEHs). This location houses three faculty and six graduate student offices, two high-resolution and high-fidelity driving simulators, work stations for up to ten research assistants, two conference rooms, and a mass testing space. The Center for Distracted Driving Research has also recently acquired an off-campus office space for additional parking of tested vehicles and research assistant work stations.