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  4. A study of subway passengers' attitudes toward congestion pricing schemes in NYC based on survey data and lessons learned from previous congestion pricing practices

A study of subway passengers' attitudes toward congestion pricing schemes in NYC based on survey data and lessons learned from previous congestion pricing practices

File(s)
Luo_cornell_0058O_10826.pdf (1.12 MB)
Permanent Link(s)
https://doi.org/10.7298/9tpn-xv37
https://hdl.handle.net/1813/70234
Collections
Cornell Theses and Dissertations
Author
Luo, Jinyu
Abstract

In 2017, Governor Andrew Cuomo declared a state of emergency due to the severe overcrowding, delays, and funding deficits with mass transit, and proposed a congestion pricing plan for vehicular traffic in parts of Manhattan to raise funds for the rapid transit system. This study explores and identifies the factors that affect the passenger’s attitudes toward the proposed scheme, both via literature review and statistical modeling. We not only include standard logistic regression models to investigate the interrelationship between public support and the selected influencing factors, but we also set up the random parameter models to incorporate random effect to account for the preference heterogeneity. Our results indicate apparent individual heterogeneities regarding the value of premium/toll when we consider public support toward congestion pricing, and present the determinants of public support such as age, gender, being single, leasing a car, and comfort satisfaction. KEYWORDS: New York City Subway, congestion pricing, public support, logistic regression model, random parameter, individual heterogeneity.

Description
86 pages
Date Issued
2020-05
Keywords
congestion pricing
•
individual heterogeneity
•
logistic regression model
•
New York City Subway
•
public support
•
random parameter
Committee Chair
Alvarez Daziano, Ricardo
Committee Member
Rossiter, David
Degree Discipline
Civil and Environmental Engineering
Degree Name
M.S., Civil and Environmental Engineering
Degree Level
Master of Science
Type
dissertation or thesis
Link(s) to Catalog Record
https://catalog.library.cornell.edu/catalog/13254488

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