Impact of Adaptive Traffic Signals on Traffic Congestion in Midtown Manhattan: A Propensity Score Matching Approach
With increasing urbanization, traffic issues have become a significant challenge for cities worldwide. This study employs Propensity Score Matching (PSM) to analyze the impact of Adaptive Traffic Signal (ATS) systems on traffic congestion in Manhattan, using data from the "Midtown in Motion" initiative. Data from New York City's Automated Traffic Volume Recording System (ATVRS) was used to assess changes in traffic flow before and after ATS implementation. Findings indicate that ATS effectively reduces peak-hour congestion and enhances flow, demonstrating its positive effect in easing urban traffic stress.
Authors
- Zongyang Zhao (ORCID: https://orcid.org/0000-0002-0318-3549)
Institutions
- Columbia University (US)
Publication Details
- Journal
- Applied and Computational Engineering
- Published
- 2024-12-06
- DOI
- https://doi.org/10.54254/2755-2721/2024.melb17903
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00