Dr. Yafeng Yin is a Professor at Department of Civil and Environmental Engineering, and Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor. He works in the area of transportation systems analysis and modeling, and has published more than 100 refereed papers in leading academic journals. Dr. Yin is the Editor-in-Chief of Transportation Research Part C: Emerging Technologies, Department Editor of Service Science, and Associate Editor of Transportation Science. He also serves on the International Advisory Committee of the International Symposium of Transportation and Traffic Theory (ISTTT). Dr. Yin received his Ph.D. from the University of Tokyo, Japan in 2002, his master’s and bachelor’s degrees from Tsinghua University, Beijing, China in 1996 and 1994 respectively. Prior to his current appointment at the University of Michigan, he was a faculty member at University of Florida between 2005 and 2016. He worked as a postdoctoral researcher and then assistant research engineer at University of California at Berkeley between 2002 and 2005. Between 1996 and 1999, he was a lecturer at Tsinghua University. Dr. Yin has received recognition from different institutions. He was one of the five recipients of the 2012 Doctoral Mentoring Award from University of Florida in recognition of his outstanding graduate student advising and mentoring. One of his papers won the 2016 Stella Dafermos Best Paper Award and the Ryuichi Kitamura Paper Award from Transportation Research Board.
Ride-sourcing companies such as Uber, Lyft and Didi Chuxing are transforming the way people travel in cities. The companies provide ride-hailing applications that intelligently match riders to drivers; drivers are private car owners who drive their own vehicles to provide ride-for-hire services for profit. Since their advent in 2009, ride-sourcing companies have enjoyed huge success, but also created many controversies. In this talk, I will present research findings from a series of studies conducted by the Lab for Innovative Mobility Systems (LIMOS) since 2014, aiming to investigate the operations of ride-sourcing services, understand their impacts and implications, and develop policies to guide their deployment and manage their operations. I plan to discuss two specific issues. I will first present a macroscopic modeling framework for analyzing the ride-sourcing market and then derive insight for its regulatory policies. We then shift our focus to the supply side of the ride-sourcing system. By viewing it as an input/output system, I show that the output rate of the ride-system system (i.e., the number of riders arriving at their destinations per unit of time) can decline with accumulation (i.e., the number of riders in the system), and then discuss how control can avoid it.