Cycling Safety: From Crash Data Analysis to a Naturalistic Cycling Study

The safety issues of cycling have become an increasing concern. This presentation, led by Drs. Shan Bao and Fred Feng, 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 and GPS and was given to study participants as a substitute for their own bicycle. 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.

More about this research: https://myumi.ch/jxl0N

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About the speakers:

Dr. Bao is an Associate Professor in the Industrial and Manufacturing Systems Engineering Department, University of Michigan-Dearborn, with a joint appointment as Associate Research Scientist in the University of Michigan Transportation Research Institute’s Human Factors Group. She is also an affiliated faculty member with UM Civil and Environmental Engineering department, MIDAS and UM Robotics Institute. Dr. 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 journals 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 is an Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering at the University of Michigan-Dearborn. He is also an affiliate faculty of Michigan Institute for Data Science (MIDAS). Dr. 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 PhD (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.