Caltech Young Investigators Lecture

Monday April 8, 2019 4:00 PM

Spatio-Temporal Pricing for Ridesharing Platforms

Location: Annenberg 105

Abstract: In this talk, I present my work on matching and pricing for ridesharing platforms, where drivers' strategic behavior (e.g. cherry-picking trips, and declining trips to chase surge prices) undercut their stated mission of providing transportation as reliable as running water." I introduce the Spatio-Temporal Pricing mechanism, which uses information about supply and demand over a planning horizon, solves for the welfare-optimal matching, and sets prices that are smooth" in both space and time. In this way, the mechanism aligns incentives for drivers and promotes reliability without using penalties or time-extended contracts always accepting all trip dispatches forms a subgame-perfect equilibrium among the drivers. The mechanism also satisfies fairness properties, including that drivers at the same location and time do not envy each other's continuation payoffs. The mechanism is also robust, in that it achieves optimality along with other axiomatic properties from any history onward, including after a deviation. Simulation analysis suggests that the STP mechanism can achieve significantly higher social welfare than a myopic pricing mechanism.

Bio: Hongyao Ma is a Ph.D. candidate in Computer Science in the Paulson School of Engineering and Applied Sciences at Harvard, advised by Prof. David C. Parkes. Her research is broadly situated at the intersection of economics and computer science, and draws on concepts from multi-agent systems and game theory. She is particularly interested in designing market-based systems to bring people together in useful ways, in the presence of uncertainty, self-interest, and autonomy. Ma is a recipient of the Siebel Scholarship, Harvard SEAS fellowship, the UCLA-CSST scholarship, and the Derek Bok Center Certificate of Distinction in Teaching at Harvard. Ma received her M.S. in 2014 at Harvard, and B.E. in 2012 at Xi'an Jiaotong University, both in Electrical Engineering. She interned at Uber in the summer of 2017, visited Technion in the summer of 2016, worked as a research intern at AT&T Labs Research in the summer of 2013, and visited UCLA as a part of the CSST Program in 2011.

This lecture is part of the Young Investigators Lecture Series sponsored by the Caltech Division of Engineering & Applied Science.

Series Caltech Young Investigators Lecture Series

Contact: Diane Goodfellow diane@cs.caltech.edu