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Examination of New York City Transit’s Bus and Subway Ridership Trends During the COVID-19 Pandemic
3 references·5 citing·37 second hop
Examination of New York City Transit’s Bus and Subway Ridership Trends During the COVID-19 Pandemic (2021)Examination of New York City Transit’s Bu…Time-Expanded Network Model of Train-Level Subway Ridership Flows Using Actual Train Movement Data (2016)Time-Expanded Network Model o…USES OF ARCHIVED AVL-APC DATA TO IMPROVE TRANSIT PERFORMANCE AND MANAGEMENT: REVIEW AND POTENTIAL (2003)USES OF ARCHIVED AVL-APC DATA…Automatic Passenger Counter Evaluation: Implications for National Transit Database Reporting (2003)Automatic Passenger Counter E…Discovering impacts of built environment on transit ridership in the post-COVID era: policy intervention and nonlinear dynamics (2025)Discovering impacts of built …Trends in Toronto’s Subway Ridership Recovery: An Exploratory Analysis of Wi-Fi Records (2024)Trends in Toronto’s Subway Ri…Navigating the post-pandemic urban landscape: Disparities in transportation recovery & regional insights from New York City (2024)Navigating the post-pandemic …Mode-specific impacts of social distancing measures on the intra- and inter-urban mobility of public transit in Seoul during the COVID-19 pandemic (2023)Mode-specific impacts of soci…Analyzing demand reduction and recovery of major rail stations in Japan during COVID-19 using mobile spatial statistics (2023)Analyzing demand reduction an…Great planning disasters (1980)Out of Control (1995)Origin and Destination Estimation in New York City with Automated Fare System Data (2002)Effects of Bus Stop Consolidation on Passenger Activity and Transit Operations (2006)The potential impact of automated data collection systems on urban public transport planning. (2008)Limited-stop bus service: an evaluation of an implementation strategy (2010)Bus Transit Operations Control: Review and an Experiment Involving Tri-Met's Automated Bus Dispatching System (2001)An Offline Framework for Handling Automatic Passenger Counting Raw Data (2014)Understanding Transit System Performance Using AVL-APC Data: An Analytics Platform with Case Studies for the Pittsburgh Region (2018)The interplay between dockless bikeshare and bus for small-size cities in the US: A case study of Ithaca (2021)Optimal strategies: A new assignment model for transit networks (1989)Estimating a Rail Passenger Trip Origin‐Destination Matrix Using Automatic Data Collection Systems (2007)Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand (2013)Approaches, technologies and importance of analysis of the number of train travellers (2019)Data-Driven Approaches to Mining Passenger Travel Patterns: “Left-Behinds” in a Congested Urban Rail Transit Network (2019)Passenger-Centric Performance Metrics for the New York City Subway (2019)Interpretation of the Correlation Coefficient: A Basic Review (1990)How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: Evidence from longitudinal data in the Netherlands (2020)The effect of COVID-19 and subsequent social distancing on travel behavior (2020)Changes in inter-city car travel behavior over the course of a year during the COVID-19 pandemic: A decision tree approach (2024)An evaluation of the long-term effects of the COVID-19 pandemic on public transit use in the United States (2025)Choice behavior of commuters' rail transit mode during the COVID-19 pandemic based on logistic model (2020)Changes in local travel behaviour before and during the COVID-19 pandemic in Hong Kong (2021)Will Covid-19 put the public back in public transport? A UK perspective (2021)Railway-station-area vitality in response to COVID-19: A case study of diverse Japanese cities (2025)Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 (2025)Who Belongs in the Family? (1953)COVID-19 and Public Transportation: Current Assessment, Prospects, and Research Needs (2020)Understanding the spatiotemporal response of dockless bike-sharing travel behavior to the small outbreaks of COVID-19 (2025)Bikeshare and subway ridership changes during the COVID-19 pandemic in New York City (2021)Impacts of COVID-19 on public transit ridership (2021)Public transit use in the United States in the era of COVID-19: Transit riders’ travel behavior in the COVID-19 impact and recovery period (2021)Travelers’ Propensity to Use Intercity Railway Services in Emerging Economies: Significance of Passengers’ Satisfaction and Communication Technologies (2024)A comparative study of machine learning classifiers for modeling travel mode choice (2017)Exploring the impacts of COVID-19 on travel behavior and mode preferences (2020)Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models (2020)Which Distance-Decay Function Can Improve the Goodness of Fit of the Metro Station Ridership Regression Model? A Case Study of Beijing (2025)
this work references cited by second hop

References

  • 2003USES OF ARCHIVED AVL-APC DATA TO IMPROVE TRANSIT PERFORMANCE AND MANAGEMENT: REVIEW AND POTENTIAL69 cited
  • 2003Automatic Passenger Counter Evaluation: Implications for National Transit Database Reporting42 cited
  • 2016Time-Expanded Network Model of Train-Level Subway Ridership Flows Using Actual Train Movement Data17 cited

Cited by

  • 2023Mode-specific impacts of social distancing measures on the intra- and inter-urban mobility of public transit in Seoul during the COVID-19 pandemic10 cited
  • 2023Analyzing demand reduction and recovery of major rail stations in Japan during COVID-19 using mobile spatial statistics9 cited
  • 2024Navigating the post-pandemic urban landscape: Disparities in transportation recovery & regional insights from New York City8 cited
  • 2025Discovering impacts of built environment on transit ridership in the post-COVID era: policy intervention and nonlinear dynamics5 cited
  • 2024Trends in Toronto’s Subway Ridership Recovery: An Exploratory Analysis of Wi-Fi Records5 cited

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