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Data-Driven Approach for Measuring and Managing Physical Distancing in Subways during Pandemic Conditions
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Data-Driven Approach for Measuring and Managing Physical Distancing in Subways during Pandemic Conditions (2023)Data-Driven Approach for Measuring and Ma…Exploring for Route Preferences of Subway Passengers Using Smart Card and Train Log Data (2022)Exploring for Route Preferenc…Activity-based TOD typology for seoul transit station areas using smart-card data (2022)Activity-based TOD typology f…Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada (2021)Slowing the spread of COVID-1…Seat Assignments With Physical Distancing in Single-Destination Public Transit Settings (2021)Seat Assignments With Physica…Exploring the Behaviour Change of Crowding Impedance on Public Transit due to COVID-19 Pandemic: Before and After Comparison (2021)Exploring the Behaviour Chang…Development of Estimating Methodology for Transit Accessibility Using Smart Card Data (2021)Development of Estimating Met…An estimation of the effects of social distancing measures on transit vehicle capacity and operations (2021)An estimation of the effects …Valuation of Metro Crowding Considering Heterogeneity of Route Choice Behaviors (2020)Valuation of Metro Crowding C…The impacts of COVID-19 pandemic on public transit demand in the United States (2020)The impacts of COVID-19 pande…Public transport planning adaption under the COVID-19 pandemic crisis: literature review of research needs and directions (2020)Public transport planning ada…COVID-19 and Public Transportation: Current Assessment, Prospects, and Research Needs (2020)COVID-19 and Public Transport…Containing COVID-19 through physical distancing: the impact of real-time crowding information (2020)Containing COVID-19 through p…Assessing transit competitiveness in Seoul considering actual transit travel times based on smart card data (2019)Assessing transit competitive…Smart card data use in public transit: A literature review (2011)Smart card data use in public…The structure of random utility models (1977)The structure of random utili…Individual Choice Behavior (1962)Conditional logit analysis of qualitative choice behavior (1972)Elimination by aspects: A theory of choice. (1972)Using Choice Experiments to Value the Environment (1998)Discrete Choice Methods and their Applications to Short Term Travel Decisions (1999)Contemporary Guidance for Stated Preference Studies (2017)Property, Privacy, and Personal Data (2004)Estimation of a disaggregate multimodal public transport Origin–Destination matrix from passive smartcard data from Santiago, Chile (2012)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Car travel time and accessibility by bus to general practitioner services: a study using patient registers and GIS (2002)Mining smart card data for transit riders’ travel patterns (2013)The cost of equity: Assessing transit accessibility and social disparity using total travel cost (2016)Estimating Express Train Preference of Urban Railway Passengers Based on Extreme Gradient Boosting (XGBoost) using Smart Card Data (2021)Investigation of modal integration of bike-sharing and public transit in Seoul for the holders of 365-day passes (2022)Evaluation of urban nightlife attractiveness for Millennials and Generation Z (2024)Impact of the COVID-19 pandemic on travel behavior in Istanbul: A panel data analysis (2020)Impacts of COVID-19 on public transport ridership in Sweden: Analysis of ticket validations, sales and passenger counts (2020)Inequality in the impact of the coronavirus shock: Evidence from real time surveys (2020)Discrete Choice Methods with Simulation (2001)Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand (2013)Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice (2013)I can board, but I’d rather wait: Active boarding delay choice behaviour analysis using smart card data in metro systems (2023)Understanding passenger route choice behavior under the influence of detailed route information based on smart card data (2023)Understanding commuting patterns using transit smart card data (2016)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)The impact of the COVID-19 pandemic on people's mobility: A longitudinal study of the U.S. from March to September of 2020 (2021)Why has public transit ridership declined in the United States? (2022)A nationwide survey of psychological distress among Chinese people in the COVID‐19 epidemic: implications and policy recommendations (2020)The socio-economic implications of the coronavirus pandemic (COVID-19): A review (2020)Cycling in the Era of COVID-19: Lessons Learnt and Best Practice Policy Recommendations for a More Bike-Centric Future (2021)Public transport for smart cities: Recent innovations and future challenges (2022)The Economics of Urban Transportation (2007)Effects of COVID-19 on rail passengers’ crowding perceptions (2021)Public transit travel choice in the post COVID-19 pandemic era: An application of the extended Theory of Planned behavior (2022)Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands (2022)The effect of COVID-19 and subsequent social distancing on travel behavior (2020)The link between bike sharing and subway use during the COVID-19 pandemic: The case-study of New York's Citi Bike (2020)Application of Protection Motivation Theory to Quantify the Impact of Pandemic Fear on Anticipated Postpandemic Transit Usage (2022)The Anticipated Use of Public Transport in the Post-Pandemic Era: Insights from an Academic Community in Thessaloniki, Greece (2022)Modeling the resilience of urban mobility when exposed to the COVID-19 pandemic: A qualitative system dynamics approach (2023)Travel Time and Transfer Analysis Using Transit Smart Card Data (2010)Validating travel behavior estimated from smartcard data (2014)Crowding cost estimation with large scale smart card and vehicle location data (2016)Exploring Transit Use during COVID-19 Based on XGB and SHAP Using Smart Card Data (2022)eXplainable DEA approach for evaluating performance of public transport origin-destination pairs (2024)Iterative DEA for public transport transfer efficiency in a super-aging society (2025)
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References

  • 1977The structure of random utility models1,732 cited
  • 2011Smart card data use in public transit: A literature review930 cited
  • 2020COVID-19 and Public Transportation: Current Assessment, Prospects, and Research Needs779 cited
  • 2020Public transport planning adaption under the COVID-19 pandemic crisis: literature review of research needs and directions479 cited
  • 2020The impacts of COVID-19 pandemic on public transit demand in the United States297 cited
  • 2021Exploring the Behaviour Change of Crowding Impedance on Public Transit due to COVID-19 Pandemic: Before and After Comparison91 cited
  • 2021Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada78 cited
  • 2019Assessing transit competitiveness in Seoul considering actual transit travel times based on smart card data44 cited
  • 2020Valuation of Metro Crowding Considering Heterogeneity of Route Choice Behaviors33 cited
  • 2022Exploring for Route Preferences of Subway Passengers Using Smart Card and Train Log Data30 cited
  • 2020Containing COVID-19 through physical distancing: the impact of real-time crowding information28 cited
  • 2021Seat Assignments With Physical Distancing in Single-Destination Public Transit Settings24 cited
  • 2021An estimation of the effects of social distancing measures on transit vehicle capacity and operations19 cited

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  • 2021Development of Estimating Methodology for Transit Accessibility Using Smart Card Data16 cited
  • 2022Activity-based TOD typology for seoul transit station areas using smart-card data13 cited
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