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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of Adaptive Traffic Signals on Traffic Congestion in Midtown Manhattan: A Propensity Score Matching Approach

Zongyang Zhao
Applied and Computational Engineering
Traffic Prediction and Management Techniques
article

Impact of Adaptive Traffic Signals on Traffic Congestion in Midtown Manhattan: A Propensity Score Matching Approach

Zongyang Zhao
article en

Abstract

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.

Applied and Computational EngineeringVol. 110(1)
Columbia University (US)
Sustainable cities and communities
Openalex Percentile: Top 76%
Traffic Prediction and Management Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.