Agent-based Simulation Evaluation of CBD Tolling: A Case Study from New York City

TL;DR

This paper tackles the problem of evaluating CBD congestion pricing in a dense urban setting by leveraging an agent-based transport model (MATSim) with a road-pricing extension. It deploys a base toll plan for Manhattan's CBD within a finely-grained MATSim-NYC test bed built from OpenStreetMap, GTFS, and a synthetic population (~8.24 million people, ~30 million trips) to analyze agent-level responses, including mode choice, route and departure-time decisions, and trip satisfaction via the scoring function. Results indicate that tolling can reduce private car use, encourage public transit and other modes, and mitigate peak-hour congestion, though link-level effects are mixed due to rerouting; the average trip score improves modestly, and broader network effects depend on policy design. The study demonstrates the feasibility and value of ABM-based toll-policy evaluation for dense cities and highlights opportunities for optimization-driven policy design, while acknowledging computational limits and the potential for scaling to more policy variants.

Abstract

Congestion tollings have been widely developed and adopted as an effective tool to mitigate urban traffic congestion and enhance transportation system sustainability. Nevertheless, these tolling schemes are often tailored on a city-by-city or even area-by-area basis, and the cost of conducting field experiments often makes the design and evaluation process challenging. In this work, we leverage MATSim, a simulation platform that provides microscopic behaviors at the agent level, to evaluate performance on tolling schemes. Specifically, we conduct a case study of the Manhattan Central Business District (CBD) in New York City (NYC) using a fine-granularity traffic network model in the large-scale agent behavior setting. The flexibility of MATSim enables the implementation of a customized tolling policy proposed yet not deployed by the NYC agency while providing detailed interpretations. The quantitative and qualitative results indicate that the tested tolling program can regulate the personal vehicle volume in the CBD area and encourage the usage of public transportation, which proves to be a practical move towards sustainable transportation systems. More importantly, our work demonstrates that agent-based simulation helps better understand the travel pattern change subject to tollings in dense and complex urban environments, and it has the potential to facilitate efficient decision-making for the devotion to sustainable traffic management.

Figures (8)

• Figure 1: An illustration of MATSim loop
• Figure 2: Charging region of the tolling program
• Figure 3: The distribution of the link flow during the day
• Figure 4: The distribution of the link flow during the day
• Figure 5: The distribution of the public transit passengers during the day