Game-Theoretic Considerations for Optimizing Taxi System Efficiency

Abstract

Taxi service is an indispensable part of public transport in modern cities. To support its unique features, a taxi system adopts a decentralized operation mode in which thousands of taxis freely decide their working schedules and routes. Taxis compete with each other for individual profits regardless of system-level efficiency, making the taxi system inefficient and hard to optimize. Most research into the management and economics of taxi markets has focused on modeling from a macro level the effects of and relationships between various market factors. Less has been done regarding a more important component--drivers' strategic behavior under the decentralized operation mode. The authors propose looking at the problem from a game-theoretic perspective. Combining game-theoretic solution concepts with existing models of taxi markets, they model taxi drivers' strategy-making process as a game and transform the problem of optimizing taxi system efficiency into finding a market policy that leads to the desired equilibrium.