Approximately Optimal Toll Design for Efficiency and Equity in Arc-Based Traffic Assignment Models

Chiu, Chih-Yuan

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https://hdl.handle.net/2142/130317 Copy

Description

Title

Approximately Optimal Toll Design for Efficiency and Equity in Arc-Based Traffic Assignment Models

Author(s)

Chiu, Chih-Yuan

Issue Date

2025-09-17

Keyword(s)

• Game theory
• Traffic control
• Optimization theory

Abstract

Congestion pricing policies have emerged as promising traffic management tools to alleviate traffic congestion caused by travelers’ selfish routing behaviors. The core principle behind deploying tolls is to impose monetary costs on frequently overcrowded routes, to incentivize self-interested travelers to select less easily congested routes. Recent literature has focused on toll design based on arc-based traffic assignment models (TAMs), which characterize commuters as traveling through a traffic network by successively selecting an outgoing arc from every intermediate node along their journey. However, existing tolling mechanisms predicated on arc-based TAMs often target the design of a single congestion-minimizing toll, ignoring crucial fairness considerations, such as the financial impact of high congestion fees on low-income travelers. To address these shortcomings, in this paper, we pose the dual considerations of efficiency and equity in traffic routing as bilevel optimization problems. Since such problems are in general computationally intractable to solve precisely, we construct a linear program approximation by introducing a polytope approximation for the set of all tolls that induce congestion-minimizing traffic flow patterns. Finally, we provide numerical results that validate our theoretical conclusions.

Publisher

Allerton Conference on Communication, Control, and Computing

Series/Report Name or Number

2025 61st Allerton Conference on Communication, Control, and Computing Proceedings

ISSN

2836-4503

Type of Resource

Text

Genre of Resource

Conference Paper/Presentation

Language

eng

Handle URL

https://hdl.handle.net/2142/130317&&

Copyright and License Information

Copyright 2025 is held by Chih-Yuan Chiu.

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