Yanbing Wang is a Ph.D. student in Civil Engineering at Vanderbilt University with Dr. Daniel Work. She has a B.S. degree (2018) in Civil Engineering from the University of Illinois at Urbana-Champaign. Her research focuses on traffic modeling, estimation and control, with the goal to understand the connection between individual driving behavior and the system-level traffic efficiency. She has been a recipient of the esteemed Dwight David Eisenhower Transportation Fellowship for five consecutive years. Outside of work, she likes hiking, playing music and petting neighbors' dogs.
Transportation cyber-physical systems utilizes efficient computational methods and data analytics to uncover traffic patterns and inform transportation decision-making at various scales. The connection between individual driving behavior and its impact on system-level traffic efficiency is critical to the design of infrastructure and driving assistance technologies to improve safety and efficiency. The first important step is developing efficient system identification routines that use in-vehicle sensor data to identify driving behavior in the complex environment. Furthermore, system-level traffic efficiency needs to be further understood through dense instrument of sensors as well as scalable data processing and visualization tools. My future research aims to enhance traffic corridor management by identifying safety-critical behaviors and creating comprehensive models for connected automated vehicles. This includes harnessing empirical data through ubiquitous sensing, and developing spatial-temporal modeling techniques to adaptively learn changing traffic patterns. The goal is to enable the prediction of real-time traffic and control of consensus driving behavior for safer and smoother traffic corridors.