Game-Theoretic Considerations for Optimizing Taxi System Efficiency

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.

Authors

• Jiarui Gan
• Bo An Nanyang Technological University

Keywords

• Public transportation
• Vehicles
• Game theory
• Optimization
• Biological system modeling
• Games
• Schedules
• Efficient System
• Taxi System
• Game-theoretic Considerations
• Optimization Problem
• Customer Demand
• Strategic Behavior
• Taxi Drivers
• Travel Speed
• Market Factors
• Taxi Services
• Longer Amount Of Time
• Convex Optimization
• Hessian Matrix
• Mixed Strategy
• Road Conditions
• Monetary Cost
• Optimal Price
• Charging Rate
• Bilevel Optimization
• Pure Strategy
• Types Of Cars
• Decentralized models
• taxi
• intelligent systems
• artificial intelligence