Collaborative Research: Economic Modeling and Control Methods for Next Generation Carpool Services

This NSF grant will contribute to the sustainability of the nation's future green transportation by exploring the dynamics of carpooling in urban transportation systems, considering that an individual’s choice to use a carpooling service depends on how many others choose to do so as well. The research will model new mechanisms of positive feedback in a range of settings, validate these results using data from public agencies and private firms, and leverage this information for improved control of pooled transportation systems. The knowledge obtained can be used to develop and refine pricing, taxation, and other policy strategies that can both promote pooling and reduce urban traffic congestion. Improving carpool options can also improve environmental outcomes, by reducing vehicle travel, and social equity, by providing reasonable travel times to those who cannot buy or drive a car but who do not live close to convenient transit options. The education and outreach plan includes recruiting students, especially those from underrepresented groups, to work on the research tasks and provide them with opportunities to mentor junior colleagues on research activities. The research will develop interactive web modules to describe these carpooling behaviors to a wide audience. The research will specifically focus on two mechanisms of positive feedback in carpooling. The first is hyperdemand, whereby the share of people choosing to carpool both depends on and affects traffic congestion. The second are matching externalities, whereby the quality of matches among carpoolers increases as more choose to carpool. The research will break new ground by bringing to bear tools from dynamical systems, search/matching theory and network-level traffic relations to build a robust theory of carpooling. To validate the theory, the research team will use empirical data collected from open data sources, as well as our industry partners. In addition, case studies of real policies to promote carpooling will inform the research and provide an evidence base for future work. The research activities will provide a new paradigm for modeling carpooling services and ride-hailing systems that will have significant impacts for the next generation of urban transportation systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.