Research Review with Shan Bao, Ph.D. and Fred Feng, Ph.D.
Speaker(s): Shan Bao, Ph.D., Associate Professor in Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn, Associate Research Scientist, University of Michigan Transportation Research Institute (UMTRI), Affiliated Faculty Member in Civil and Environmental Engineering, University of Michigan-Ann Arbor, Michigan Institute for Data Science (MIDAS), and Michigan Robotics
Fred Feng, Ph.D., Assistant Professor in Industrial and Manufacturing Systems Engineering, University of Michigan-Dearborn, Affiliated Faculty Member, Michigan Institute for Data Science (MIDAS)
Presentation Title: Cycling Safety: From Crash Data Analysis to a Naturalistic Cycling Study
Date/Time: Wednesday, October 27th, 2021 | 2:30 PM ET
Continuing Education Units (CEU): .1*
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Abstract: The safety issues of cycling have become an increasing concern. The presentation describes two unique studies related to cycling safety, from crash data analysis to a recent naturalistic cycling study in Ann Arbor, Michigan. The Crash Report Sampling System data was used in this study to identify significant factors that impact cyclists’ crash injury levels. In the naturalistic cycling study, a fleet of four electric bikes was instrumented with cameras, GPS and were given to study participants as a substitute for their own bicycles. A total of over 5,000 miles of riding data from 77 subjects were collected over two years. The dataset could be used for studying the interactions between motorists and cyclists on real-world roadways.
Dr. Shan Bao received her Ph.D. in mechanical and industrial engineering from the University of Iowa in 2009. Her research interests focus on human factors issues related to connected and automated vehicle technologies, ADAS system evaluation, and big data analysis. She has served as the PI or co-PI of 54 research projects. She has published 72 technical publications, including 40 refereed journal articles. Shan is a member of the Human Factors and Ergonomics Society and has served as the chair of the Surface Transportation Technical Group of Human Factors and Ergonomics Society. She is a also member of the TRB Vehicle User Characteristics Committee and the TRB Human Factors in Road Vehicle Automation subcommittee.
Dr. Fred Feng’s research focuses on advancing the safety of environmentally sustainable, healthy, and equitable modes of transportation, such as cycling, walking, and public transit, through the development of data-driven insights, strategies & tactics, and technologies. To this end, we use a variety of quantitative methodologies including behavioral data analysis, statistical learning, computational human performance modeling, and human factors. Dr. Feng earned his B.E. (2006) and M.S. (2009) at Tsinghua University in China, and his Ph.D. (2015) in Industrial and Operations Engineering from the University of Michigan, Ann Arbor. Before joining UM-Dearborn, he was a postdoctoral research fellow at the University of Michigan Transportation Research Institute (UMTRI). Dr. Feng serves on the Scientific Committee of the International Cycling Safety Conference and on the Board of Directors of Washtenaw Bicycling and Walking Coalition.