2024/07/06 by Alfredo Torrico, Natthawut Boonsiriphatthanajaroen, Torrico, Alfredo +7
Social Sciences · #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Mathematics #Optimization and Control (math.OC) #Transportation Planning and Optimization
paper · pdf · doi:10.48550/arxiv.2407.05035
openalex publication_date 2024/07/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Congestion pricing is used to raise revenues and reduce traffic and pollution. However, people have heterogeneous spatial demand patterns and willingness (or ability) to pay tolls, and so pricing may have substantial equity implications. We develop a data-driven approach to design congestion pricing given policymakers' equity and efficiency objectives. First, algorithmically, we extend the Markovian traffic equilibrium setting introduced by Baillon & Cominetti (2008) to model heterogeneous populations and incorporate prices and outside options such as public transit. In this setting, we show that a unique equilibrium exists. Second, via a detailed case study, we empirically evaluate various pricing schemes using data collected by an industry partner in the city of Bogota, one of the most congested cities in the world. We find that pricing personalized to each economic stratum can be substantially more efficient and equitable than uniform pricing; however, non-personalized but area-based pricing can recover much of the gap.