Our ResearchGuided by a theory-practice model, our empirical research focus is twofold: (1) to examine fundamental theoretical questions on spatial, selective, and sustained attention that grow from hypotheses about real-world problems in driving and interface design; (2) to apply the understanding of cognitive and neural mechanisms of attention to practical problems such as aging and driving, distraction and engagement, driver-automation interaction, remote operation, and information visualization. Our areas of research include:
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Projects
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Remote Operation of Automated Vehicles
In the recent years, remote operation has already been integrated into Robotaxi services, the trucking industry, and the deployment of roadside robots. Such operators could be tasked to monitor, assist, or even directly control vehicles. Although remote operation is expected to make the transportation services safer and more efficient, significant human factors challenges exist in remote operation setup and interface design, staffing arrangement, operator workload, and training. To address the challenges, we propose a novel approach of proactive remote operation to support operator anticipation and engagement. Our studies also investigate operator cognitive capabilities and task interface design. Our findings suggest that human operators can monitor two vehicles simultaneously, while they are more likely to miss events such as automation missing a road sign among various automation failures. With the support from NC Department of Transportation, our lab collaborates with Civil Engineering to examine state's regulations of Robotaxi and remote operation. Book chapter on Proactive Remote Operation [summary slides] Our Recent Findings on Operator Capability and Testing Method |
Keeping Drivers Engaged when Using Partial (L2) Automation
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As partially automated driving systems (SAE Level 2) become more prevalent, maintaining driver engagement remains a critical safety challenge because these systems still require continuous human monitoring to handle potential technological failures. Drivers often experience underload or become distracted by non-driving-related tasks (NDRTs), which can lead to decreased vigilance, mind wandering, and compromised takeover performance. This line of research explores the effectiveness of intermittent conversational prompts, especially those that require processing driving-related information, as a method to enhance cognitive engagement and ensure drivers remain "in the loop". Our research also explores measures of cognitive engagement as it is much more difficult to quantify than visual or manual engagement. A Measure of Cognitive Engagement via Non-Driving-Related Tasks Conversational Prompts for Driver Engagement [press release] |
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Mind Wandering and Driving Safety
Our minds often leave the present experience and wander around self-generated thoughts and feelings. When the mind wanders, attention drifts away from task-relevant perceptual information, leading to deteriorated performance on the task at hand. This research seeks to understand the environmental and individual factors that influence the experience of mind wandering and its impact of task performance. Our studies found bi-directional interplay between mind wandering and the task at hand. On the one hand, mind wandering affects task performance such as our driving speed fluctuates more when the mind wanders. On the other hand, the task also influences our mind wandering experience. For example, we are more likely to mind wander in a monotonous environment and whether we mind wander in images or an audio book depends on the task. Environment Complexity Impacts Driver Mind Wandering [press release] Mind Wanders in Visual and Auditory Modalities |
Message Delivery in Manual and Automated Driving
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As highly automated cars become more prominent, future drivers likely won’t pay as much attention to the road. Supported by a grant from the NC Department of Transportation, our lab collaborates with Industrial and Systems Engineering and the Institute for Transportation Research and Education to investigate the future presentation of road signage. This project examines the influence of in-vehicle dynamic message displays of trip-related but non-safety critical information on driver visual behavior and performance, as compared with conventional on-road guide or logo sign use, during manual and highly automated driving. Driver Visual Behavior When Using In-Vehicle and Roadside Service Logo Signs Presenting Non-Safety Related Information during Automated Driving |
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Pinpoint the Needs of Older Drivers
This project aims to help older drivers understand what cognitive changes come with age and how do these changes affect driving. Funded by the N.C. Governor’s Highway Safety Program, an NC State Faculty research award, and a scholarship from the Aging Technical Group of the Human Factors and Ergonomics Society, our lab partners with the UNC Highway Safety Research Institute and developmental psychologists to develop programs and countermeasures to reduce the crash risks of older drivers and to improve road safety. Our goal is to identify assessment and training methods for older drivers. That could mean pointing out typical driving situations that pose more risk to an individual experiencing decline in attention. Our Drive Aware Task and Recent Findings Our Findings on Attention Networks and Crash Risks in Specific Situations The Attentional Failure during Driving Questionnaire (AFDQ) [pdf] [excel] |
Attention & Hazard Detection
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It is well known that traffic collisions can easily occur when a driver’s attention is consumed by task irrelevant information (e.g. cellphone, or billboards). It is also possible though that drivers will fail to identify certain hazards or traffic signals because their focus is consumed by other, equally, pertinent events on the road. Our research aims to explore when and why drivers miss critical road hazards, potential physiological markers of hazard detection, and how to mitigate the cognitive distortions. This line of research also examines attentional process has a moment-to-moment measure of driver trust in vehicle automation. Our Recent Findings on Visual Search and Hazard Detection How Detecting One Hazard Hinders a Driver's Capability to Find a Second? The Interplay Between Trust and Attention in Driver Monitoring of Automation |
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Understanding Wearers' Interaction with Intelligent Prostheses
In projects led by colleagues from Biomedical Engineering, our lab conducts research on wearer interaction with intelligent lower-limb prostheses. This line of work primarily focuses on applying human factors principles to understand the complex dynamics between amputees and the intelligent devices. These projects expand our lab's application of psychological science to additional technological contexts outside transportation. To promote wearer acceptance and adoption, we contextualize the usability framework to intelligent prostheses. We also develop and validate human factors measures including mapping visuospatial attention, quantifying cognitive workload, and uncovering wearer preference during self-tuning. Supported by grants from both the National Science Foundation (NSF) and the National Institutes of Health (NIH), this research aims to harmonize the interaction between the wearer, the device, and the environment to improve the wearer's quality of life. A Usability Framework for Wearer Interaction with Intelligent Prostheses A Novel Measure of Visuospatial Attention during Walking Understanding Wearer Preference via Think-Aloud and Thematic Analysis Auditory Stroop as a Cognitive Workload Measure |