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Short-Term Prediction of Ridership on Public Transport with Smart Card Data
13 references·16 citing·26 second hop
Short-Term Prediction of Ridership on Public Transport with Smart Card Data (2015)Short-Term Prediction of Ridership on Pub…Mining smart card data for transit riders’ travel patterns (2013)Mining smart card data for tr…Estimation of a disaggregate multimodal public transport Origin–Destination matrix from passive smartcard data from Santiago, Chile (2012)Estimation of a disaggregate …Smart card data use in public transit: A literature review (2011)Smart card data use in public…Review and meta-analysis of U.K. time elasticities of travel demand (2011)Review and meta-analysis of U…Bus Passenger Origin-Destination Estimation and Related Analyses Using Automated Data Collection Systems (2011)Bus Passenger Origin-Destinat…Analyzing Multimodal Public Transport Journeys in London with Smart Card Fare Payment Data (2009)Analyzing Multimodal Public T…Use of Smart Card Data to Define Public Transit Use in Seoul, South Korea (2008)Use of Smart Card Data to Def…Measuring transit use variability with smart-card data (2007)Measuring transit use variabi…Individual Trip Destination Estimation in a Transit Smart Card Automated Fare Collection System (2007)Individual Trip Destination E…Using Archived AVL-APC Data to Improve Transit Performance and Management (2006)Using Archived AVL-APC Data t…The potential of public transport smart card data (2005)The potential of public trans…The demand for public transport: a practical guide (2004)The demand for public transpo…Public transport values of time (2004)Public transport values of ti…Identifying human mobility patterns using smart card data (2023)Identifying human mobility pa…“Who can I ask for help?”: Mechanisms behind digital inequality in public transport (2023)“Who can I ask for help?”: Me…Path-oriented synchronized transit scheduling using time-dependent data (2022)Path-oriented synchronized tr…Estimating on-board passenger comfort in public transport vehicles using incomplete automatic passenger counting data (2022)Estimating on-board passenger…Multi-city exploration of built environment and transit mode use: Comparison of Melbourne, Amsterdam and Boston (2021)Multi-city exploration of bui…Examining circuity of urban transit networks from an equity perspective (2021)Examining circuity of urban t…Personalized predictive public transport crowding information with automated data sources (2020)Personalized predictive publi…On demand forecasting of demand-responsive paratransit services with prior reservations (2020)On demand forecasting of dema…Passenger Travel Time Reliability for Multimodal Public Transport Journeys (2019)Passenger Travel Time Reliabi…Workshop 8 report: Big data in the digital age and how it can benefit public transport users (2018)Workshop 8 report: Big data i…Constructing Spatiotemporal Load Profiles of Transit Vehicles with Multiple Data Sources (2018)Constructing Spatiotemporal L…Unraveling traveler mobility patterns and predicting user behavior in the Shenzhen metro system (2017)Unraveling traveler mobility …Improving predictions of public transport usage during disturbances based on smart card data (2017)Improving predictions of publ…Constructing Transit Origin–Destination Matrices with Spatial Clustering (2017)Constructing Transit Origin–D…A Bayesian Additive Model for Understanding Public Transport Usage in Special Events (2016)A Bayesian Additive Model for…Data driven improvements in public transport: the Dutch example (2015)Data driven improvements in p…The measurement of urban travel demand (1974)Passenger perceptions and the ideal urban bus journey experience (2007)Transport and its infrastructure (2007)Travel satisfaction with public transport: Determinants, user classes, regional disparities and their evolution (2016)Estimating a Rail Passenger Trip Origin‐Destination Matrix Using Automatic Data Collection Systems (2007)Automated Inference of Linked Transit Journeys in London Using Fare-Transaction and Vehicle Location Data (2013)Analyzing year-to-year changes in public transport passenger behaviour using smart card data (2017)Transport modelling in the age of big data (2017)Geography: A Modern Synthesis (1972)Geography: a modern synthesis (2004)Spatiotemporal Patterns of Urban Human Mobility (2012)Behavioural data mining of transit smart card data: A data fusion approach (2014)Property, Privacy, and Personal Data (2004)Observing the rhythms of daily life: A six-week travel diary (2002)Introduction: Habitual travel choice (2003)Passenger Segmentation Using Smart Card Data (2014)Zooming into individuals to understand the collective: A review of trajectory-based travel behaviour studies (2014)Inferring patterns in the multi-week activity sequences of public transport users (2016)The promises of big data and small data for travel behavior (aka human mobility) analysis (2016)Understanding commuting patterns using transit smart card data (2016)A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership (2018)Clustering Smart Card Data for Urban Mobility Analysis (2016)Detecting the dynamics of urban structure through spatial network analysis (2014)Valuation of travel time (2012)Value of travel time reliability: A review of current evidence (2012)Crowding valuation in urban tram and bus transportation based on smart card data (2018)
this work references cited by second hop

References

  • 2011Smart card data use in public transit: A literature review930 cited
  • 2004Public transport values of time626 cited
  • 2013Mining smart card data for transit riders’ travel patterns606 cited
  • 2012Estimation of a disaggregate multimodal public transport Origin–Destination matrix from passive smartcard data from Santiago, Chile528 cited
  • 2004The demand for public transport: a practical guide452 cited
  • 2005The potential of public transport smart card data396 cited
  • 2007Individual Trip Destination Estimation in a Transit Smart Card Automated Fare Collection System372 cited
  • 2007Measuring transit use variability with smart-card data271 cited
  • 2011Bus Passenger Origin-Destination Estimation and Related Analyses Using Automated Data Collection Systems217 cited
  • 2009Analyzing Multimodal Public Transport Journeys in London with Smart Card Fare Payment Data180 cited
  • 2006Using Archived AVL-APC Data to Improve Transit Performance and Management101 cited
  • 2008Use of Smart Card Data to Define Public Transit Use in Seoul, South Korea98 cited
  • 2011Review and meta-analysis of U.K. time elasticities of travel demand93 cited

Cited by

  • 2023Identifying human mobility patterns using smart card data61 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2016A Bayesian Additive Model for Understanding Public Transport Usage in Special Events53 cited
  • 2022Estimating on-board passenger comfort in public transport vehicles using incomplete automatic passenger counting data49 cited
  • 2019Passenger Travel Time Reliability for Multimodal Public Transport Journeys47 cited
  • 2017Improving predictions of public transport usage during disturbances based on smart card data45 cited
  • 2020Personalized predictive public transport crowding information with automated data sources45 cited
  • 2021Multi-city exploration of built environment and transit mode use: Comparison of Melbourne, Amsterdam and Boston41 cited
  • 2017Constructing Transit Origin–Destination Matrices with Spatial Clustering40 cited
  • 2023“Who can I ask for help?”: Mechanisms behind digital inequality in public transport38 cited
  • 2015Data driven improvements in public transport: the Dutch example37 cited
  • 2017Unraveling traveler mobility patterns and predicting user behavior in the Shenzhen metro system37 cited
  • 2020On demand forecasting of demand-responsive paratransit services with prior reservations29 cited
  • 2022Path-oriented synchronized transit scheduling using time-dependent data26 cited
  • 2018Workshop 8 report: Big data in the digital age and how it can benefit public transport users24 cited
  • 2018Constructing Spatiotemporal Load Profiles of Transit Vehicles with Multiple Data Sources23 cited
  • 2021Examining circuity of urban transit networks from an equity perspective22 cited