To Wednesday 25 April 2018 - 13:30
Ridesharing platforms match drivers and riders to trips, using dynamic prices to balance supply and demand. Because drivers work at-will, and are free to accept or decline trips, a challenge is to align incentives, so that drivers will always accept dispatched trips. We introduce the Spatio-Temporal Pricing (STP) mechanism, which makes use of anonymous, origin-destination (OD) prices, and is subgame-perfect incentive compatible, welfare-optimal, envy-free, and budget balanced. We assume impatient riders, drivers who remain in the system past the end of the planning horizon, and complete information about supply and demand. The proof of incentive alignment makes use of concavity properties of min-cost flow objectives. We also give an impossibility result, that there can be no dominant-strategy mechanism with the same economic properties.
Joint work with Fei Fang (CMU) and Hongyao Ma (Harvard).
The lecture is given as part of the Israel Pollak Distinguished Lecture Series 2018