Yi-Ching Lee

Assistant Professor

Human Factors/Applied Cognition: Human factors in transportation and medical systems; social interactions; intelligent systems; intelligent virtual agents

Dr. Lee joined George Mason University in the Fall of 2016. Her areas of research interest include social interaction and communication in intelligent systems, human-automation interaction, human factors in transportation and medical systems, and behavior change, with a focus on improving quality of life and health behaviors.

She is interested in other emerging technologies, such as interactions with intelligent virtual agents in online applications and social communication through text-based media.

Her background is Industrial Engineering (PhD) and Experimental Psychology (MS). She has 10+ years of professional experience conducting empirical scientific research in human factors transportation. Her research focuses on the theoretical advancement and practical understanding of real-world behavioral issues in the context of human-technology interactions. Her research interests are centered on understanding and improving driver behavior and driver's cognitive and emotional state, using qualitative and quantitative analytical techniques as well as driving simulators and on-road instrumented vehicles (including eye-tracking and other physiological measurements).

Dr. Lee’s most significant contribution is in the development of research methodology, including integration between applied and basic research, innovative experimental design, applying theories and principles from other research domains, and adaptive analytical methods. She has served as the PI and co-PI on multiple federal grants, including one current NSF award focusing on monitoring and detecting unsafe driving behaviors among young ADHD drivers.

Prior to joining GMU, Dr. Lee directed the driving simulator research group at the Children’s Hospital of Philadelphia and successfully managed multi-institution research projects.

Selected Publications

Lee, Y.-C., Hand, S. H., & Lilly, H. (2020). Are parents ready to use autonomous vehicles to transport children? Concerns and safety features. Journal of Safety Research, 72, 287-297.

Lee, Y.-C., & Mirman, J. H. (2018). Parents’ perspectives on using autonomous vehicles to enhance children’s mobility. Transportation Research Part C: Emerging Technologies, 96: 415-431.

Lee, Y.-C., & LaVoie, N. (2018). Instruction-prompted objective behaviors as proxy for subjective measures in a driving simulator. Transportation Research Part F: Psychology and Behaviour, 55, 58-66.

Lee, Y.-C., & Winston, F. K. (2016). Stress induction techniques in a driving simulator and reactions from newly licensed drivers. Transportation Research Part F, 42, 44-55.

Ontañón, S., Lee, Y.-C., Snodgrass, S., Bonfiglio, D. J., Winston, F. K., McDonald, C. C., & Gonzalez, A. J. (2014). Case-Based prediction of teen driver behavior and skill. Case-Based Reasoning Research and Development, Lecture Notes in Artificial Intelligence, 8765, 375-489.

Lee, Y.-C., Lee, J. D., & Boyle, L. N. (2009). The interaction of cognitive load and attention-directing cues in driving. Human Factors, 51, 271-280.

Lee, Y.-C., Lee, J. D., & Boyle, L. N. (2007). Visual attention in driving: the effects of cognitive load and visual disruption. Human Factors, 49, 721-733.

Expanded Publication List

Barragan, D. & Lee, Y.-C. (in press). Individual differences predict drivers hazard perception skills. International Journal of Human Factors and Ergonomics.

Barragan, D., Peterson, M. S., & Lee, Y.-C. (2021). Hazard perception-response: A theoretical framework to explain drivers' interactions with roadway hazards. Safety, 7, 29.

Lee, Y.-C., Malcein, L. A., & Kim, S. C. (2021). Information and communications technology (ICT) usage during COVID-19: Motivating factors and implications. International Journal of Environmental Research and Public Health, 18, 3571.

Koppel, S., Lee, Y.-C., Mirman, J. H., Peiris, S., & Tremoulet, P. (2021). Key factors associated with Australian parents’ willingness to use an automated vehicle to transport their unaccompanied children. Transportation Research Part F: Traffic Psychology and Behaviour, 78, 137-152.

Li, Q., Zhao, L., Lee, Y.-C., Ye, Y., & Lin, J. (2021). CPM: A general feature dependency pattern mining framework for contrast multivariate time series. Pattern Recognition, 112, 107711. DOI: 10.1016/j.patcog.2020.107711

Lee, Y.-C., & Malcein, L. (2020). Users’ mental models for computer-mediated communication: Theorizing emerging technology and behavior in eHealth applications. Human Behavior and Emerging Technologies, 2, 354-366.

Krall, J. R., Adibah, N., Babin, L., Lee, Y.-C., Motti, V. G., McCombs, M., McWilliams, A., Thornburg, J., & Pollack, A. Z. (2020). Estimating exposure to traffic-related PM_2.5 among women commuters using vehicle and personal monitoring. Environmental Research, 187, 109644.

Lee, Y.-C. (2020). Parenting in the digital contexts: Are parents ready to use automated vehicles to transport children? In L. Benedetto (Ed.), Parenting. IntechOpen.

Li, Q., Zhao, L., Lee, Y.-C., & Lin, J. (2020). Contrast pattern mining in paired multivariate time series of controlled driving behavior experiment. ACM Transactions on Spatial Algorithms and Systems, 6, Article No. 25. https://doi.org/10.1145/3397272

Lee, Y.-C., Hand, S. H., & Lilly, H. (2020). Are parents ready to use autonomous vehicles to transport children? Concerns and safety features. Journal of Safety Research, 72, 287-297.

Conn Welch, K., Harnett, C. K., & Lee, Y.-C. (2019). A review on measuring affect with practical sensors to monitor driver behavior. Safety, 5, 72-90.

Lee, Y.-C., & Mirman, J. H. (2018). Parents’ perspectives on using autonomous vehicles to enhance children’s mobility. Transportation Research Part C: Emerging Technologies, 96: 415-431.

Lee, Y.-C., Ward McIntosh, C., Winston, F. K., Power, T. J., Huang, P., Ontañón, S., & Gonzalez, A. J. (2018). Design of an experimental protocol to examine medication non-adherence among young drivers diagnosed with ADHD: a driving simulator study. Contemporary Clinical Trials Communications, 11: 149-155.

Delgado, M. K., McDonald, C. C., Winston, F. K., Halpern, S. D., Buttenheim, A. M., Setubal, C., Huang, Y., Saulsgiver, K. A., & Lee, Y.-C. (2018). Attitudes towards technological and behavioral economic strategies to reduce cellphone use while driving among teens. Traffic Injury Prevention, 19: 569-576.

Lee, Y.-C., & LaVoie, N. (2018). Instruction-prompted objective behaviors as proxy for subjective measures in a driving simulator. Transportation Research Part F: Psychology and Behaviour, 55, 58-66.

LaVoie, N., Lee, Y.-C., Allison, A., & Parker, J. (2018). A new approach for assessing and training drivers’ speed management. Accident Analysis and Prevention, 111, 266-270.

Mirman, J. H., Durbin, D.R., Lee, Y.-C., & Seifert, S. (2017). Adolescent and adult drivers' mobile phone use while driving with different interlocutors. Accident Analysis and Prevention, 104, 18-23.

Lee, Y.-C., & Winston, F. K. (2016). Stress induction techniques in a driving simulator and reactions from newly licensed drivers. Transportation Research Part F, 42, 44-55.

Loeb, H., Chamberlain, S., and Lee, Y.-C. (2016). EyeSync - real time integration of an eye tracker in a driving simulator environment. SAE Technical Paper 2016-01-1419.

LaVoie, N., Lee, Y.-C., & Parker, J. (2016). Preliminary research developing a theory of cell phone distraction and social relationships. Accident Analysis & Prevention, 86, 155-160.

McDonald, C. C., Kandadai, V., Lee, Y.-C., Loeb, H., Seacrist, T., Bonfiglio, D., Fisher, D. L. & Winston, F. K. (2015). Evaluation of a risk awareness perception training program on novice teen driver behavior at left-turn intersections. Transportation Research Record: Journal of the Transportation Research Board, 2516, 15-21.

McDonald, C. C., Kandadai, V., Loeb, H. S., Seacrist, T. S., Lee, Y.-C., Winston, Z., & Winston, F. K. (2015). Simulated Driving Assessment (SDA) for teen drivers: Results from a validation study. Injury Prevention, 21, 145-152.

Romer, D., Lee, Y.-C., McDonald, C. C., & Winston, F. K. (2014). Adolescence, attention allocation, and driving safety. Journal of Adolescent Health, 54, S6-S15.

Mirman, J. H., Lee, Y.-C., Kay, J., Durbin, D. R., & Winston, F. K. (2012). Development of a novel web-based parent support program to improve the quantity, quality and diversity of teens' home-based pre-licensure practice driving. Transportation Research Record: Journal of the Transportation Research Board, 2318, 107-115.

McDonald, C. C., Tanenbaum, J. B., Lee, Y.-C., Fisher, D. L., Mayhew, D. R., & Winston, F. K. (2012). Using crash data to develop simulator scenarios for assessing young novice driver performance. Transportation Research Record: Journal of the Transportation Research Board, 2321, 73-78.

He, J., Becic, E., Lee, Y.-C., & McCarley, J. S. (2011). Mind wandering behind the wheel: Performance and oculomotor correlates. Human Factors, 53, 13-21.

Lee, Y.-C., Lee, J. D., & Boyle, L. N. (2009). The interaction of cognitive load and attention-directing cues in driving. Human Factors, 51, 271-280.

Redenbo, S. J. & Lee, Y.-C. (2009). The effects of cognitive and perceptual loads on driver behavior. Transportation Research Record: Journal of the Transportation Research Board, 2138, 20-27.

Lee, Y.-C., Lee, J. D., & Boyle, L. N. (2007). Visual attention in driving: the effects of cognitive load and visual disruption. Human Factors, 49, 721-733.

Schnell, T., Aktan, F., & Lee, Y.-C. (2003). Nighttime visibility and retroreflectance of pavement markings in dry, wet, and rainy conditions. Transportation Research Record: Journal of the Transportation Research Board, 1824, 144-155.

Grants and Fellowships

2019 - 2022: Driver vigilance framework for level 2 and level 3 driving automation systems, National Highway Traffic Safety Administration

2019 - 2021: Microplastics in the Mason watershed: A mass balance approach, GMU Institute for a Sustainable Earth

2018: Turning ambiguous traffic scenarios into autonomous vehicle’s intelligence, GMU OSCAR Summer Impact Grant

2017 - 2018: Interpretable temporal mining for contrastive driving behaviors, GMU Office of Research

2017 - 2018: GEST DC Study: Gestational exposure to traffic pollution in the DC metro area, GMU Office of Research

2015 - 2021: SCH:INT:Collaborative Research: Diagnostic driving: Real time driver condition detection through analysis of driving behavior, National Science Foundation

Education

PhD in Industrial Engineering (Human Factors concentration) at University of Iowa, 2006

Dissertations Supervised

Daniela Barragan, Empirical and Theoretical Understanding of Driver Hazard Perception and Response (2020)