Driver Positioning and Incentive Budgeting with an Escrow Mechanism for Ridesharing Platforms
Hao Yi Ong, Daniel Freund, Davide Crapis

TL;DR
Lyft's PPZ system uses a novel escrow mechanism and convex optimization to dynamically incentivize drivers, improving ride availability and increasing platform revenue across 320 cities.
Contribution
The paper introduces a new escrow-based incentive budgeting system and an efficient optimization algorithm for driver positioning in large-scale ridesharing.
Findings
System deployed in 320 cities within a year
Generated millions of driver bonuses weekly
Achieved a 0.5% increase in incremental bookings
Abstract
Drivers on the Lyft rideshare platform do not always know where the areas of supply shortage are in real time. This lack of information hurts both riders trying to find a ride and drivers trying to determine how to maximize their earnings opportunity. Lyft's Personal Power Zone (PPZ) product helps the company to maintain high levels of service on the platform by influencing the spatial distribution of drivers in real time via monetary incentives that encourage them to reposition their vehicles. The underlying system that powers the product has two main components: (1) a novel 'escrow mechanism' that tracks available incentive budgets tied to locations within a city in real time, and (2) an algorithm that solves the stochastic driver positioning problem to maximize short-run revenue from riders' fares. The optimization problem is a multiagent dynamic program that is too complicated to…
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