Shan Bao’s presentation at the ATLAS Center Symposium Series at Texas A&M Transportation Institute was well attended by 40 individuals. They also had three of the TTI remote offices connected via Polycom (Arlington, Austin and Dallas).
As part of the ATLAS Center Symposium Series, Texas A&M Transportation Institute is hosting UMTRI’s Shan Bao for her presentation on:
Naturalistic Driving Data Analysis: From Data to the Truth
Tuesday, November 11th
12:00 to 1:00 p.m.
Gibb Gilchrist Bldg., Room 102
Naturalistic driving studies which collect data from instrumented vehicles driven by lay drivers in real-world settings offer the promise of truly understanding driver performance and behavior in order to improve traffic safety. This includes developing an understanding of how the driver interacts with and adapts to the vehicle, traffic environment, roadway characteristics, traffic control devices, and the environment and how collision risk is influenced by these factors and their interaction. However, gaining these insights is a data-mining and statistical challenge. Dr. Bao will discuss how these data can be used to discover truths about driver performance and behavior.
Shan Bao is an assistant research scientist in UMTRI’s Human Factors Group. She joined UMTRI in 2009, starting as a postdoctoral fellow after completing her Ph.D. in industrial engineering at the University of Iowa.
Dr. Bao’s research interests focus on driver behavior modeling, driver distraction, naturalistic driving data analysis and driver-simulator study. Specifically, she has developed models of driver following and lane-keeping behavior using statistical and methodological techniques. She has also performed extensive analyses of various naturalistic driving databases to identify driver-behavior patterns and to identify predictors of crashes and near crashes that can be associated with different driver populations. Her research interests also include the use of UMTRI’s driving simulator to study and test advanced driving-safety prevention techniques.