The proliferation of smartphones in recent years has catalyzed rapid growth of app-based ride-sourcing services such as Uber, Lyft and Didi Chuxing. A big issue that arises with service expansion is the empty miles produced by ride- sourcing vehicles. To overcome the physical and temporal frictions that separate drivers from customers and effectively reposition themselves towards desired destinations, ride sourcing vehicles generate a significant amount of vacant trips. These empty miles traveled result in an inefficient use of the available fleet and increase traffic demand, posing substantially impacts on system operations. This talk expounds the operational physics underlying the empty miles in ride-sourcing services, and interprets the cause of two critical matching failures that can arise due to some common mechanisms practiced by ride-sourcing platforms. Given the prevalence of the failures in real-world operations, we discuss countermeasures to avoid inefficiencies upon the empty miles, and sustain the system performances. Massive empirical data are employed to evidence the presence of matters in reality as well as the effectiveness of control strategies discussed.

Zhengtian Xu is a Ph.D. Candidate in the Department of Civil and Environmental Engineering at the University of Michigan. His research interests mainly focus on developing novel models, tools, and conducting data-driven quantitative analyses to understand, promote, and regulate emerging mobility services and infrastructures.