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

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.