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Identifying Passengers Who Are at Risk of Reducing Public Transport Use: A Survival Time Analysis Using Smart Card Data
12 references·1 citing·35 second hopsampled
Identifying Passengers Who Are at Risk of Reducing Public Transport Use: A Survival Time Analysis Using Smart Card Data (2018)Identifying Passengers Who Are at Risk of…Transit passenger segmentation using travel regularity mined from Smart Card transactions data (2014)Transit passenger segmentatio…Behavioural data mining of transit smart card data: A data fusion approach (2014)Behavioural data mining of tr…Mining smart card data for transit riders’ travel patterns (2013)Mining smart card data for tr…Bus Dwell Time Estimation and Prediction: A Study Case in Shanghai-China (2013)Bus Dwell Time Estimation and…Spatial-Temporal Daily Frequent Trip Pattern of Public Transport Passengers Using Smart Card Data (2012)Spatial-Temporal Daily Freque…Estimation of behavioural change of railway passengers using smart card data (2012)Estimation of behavioural cha…Detection of Activities of Public Transport Users by Analyzing Smart Card Data (2012)Detection of Activities of Pu…Smart card data use in public transit: A literature review (2011)Smart card data use in public…Geodemographic analysis and the identification of potential business partnerships enabled by transit smart cards (2011)Geodemographic analysis and t…Analyzing Multimodal Public Transport Journeys in London with Smart Card Fare Payment Data (2009)Analyzing Multimodal Public T…Modeling Transit Travel Patterns from Location-Stamped Smart Card Data Using a Disaggregate Approach (2007)Modeling Transit Travel Patte…Measuring transit use variability with smart-card data (2007)Measuring transit use variabi…Issues of Development of Smart Transport Assessment Indicators (2020)Issues of Development of Smar…Rough-Fuzzy Hybridization: A New Trend in Decision Making (1999)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)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)Interactive Spatial Data Analysis (1995)Interactive spatial data analysis (1996)Applied Spatial Data Analysis with R (2013)Exploring gendered cycling behaviours within a large-scale behavioural data-set (2013)Policy analysis of third party electronic coupons for public transit fares (2014)Station-based average travel distance and its relationship with urban form and land use: An analysis of smart card data in Nanjing City, China (2019)The potential of public transport smart card data (2005)Estimating a Rail Passenger Trip Origin‐Destination Matrix Using Automatic Data Collection Systems (2007)Individual Trip Destination Estimation in a Transit Smart Card Automated Fare Collection System (2007)Spatiotemporal Patterns of Urban Human Mobility (2012)Clustering Smart Card Data for Urban Mobility Analysis (2016)DWELL TIME RELATIONSHIPS FOR LIGHT RAIL SYSTEMS (1992)Determinants of Bus Dwell Time (2004)Prediction Model of Bus Arrival and Departure Times Using AVL and APC Data (2004)SMARTBUS (2016)Bus-arrival time prediction using bus network data model and time periods (2018)Deep Learning Framework for Predicting Bus Delays on Multiple Routes Using Heterogenous Datasets (2020)Observing the rhythms of daily life: A six-week travel diary (2002)Public transport for smart cities: Recent innovations and future challenges (2022)Urban Transit : Operations, Planning and Economics (2005)Urban Transit: Operations, Planning and Economics (2006)Mobility as a Service: A Critical Review of Definitions, Assessments of Schemes, and Key Challenges (2017)Big Data Analytics in Intelligent Transportation Systems: A Survey (2018)Activity spaces: measures of social exclusion? (2003)Smart cities survey: Technologies, application domains and challenges for the cities of the future (2019)Introduction: Habitual travel choice (2003)Spatio-Temporal Analysis of Passenger Travel Patterns in Massive Smart Card Data (2017)Calibration of a transit route choice model using revealed population data of smartcard in a multimodal transit network (2019)Exploring the difference between ridership patterns of subway and taxi: Case study in Seoul (2017)Data-driven model for passenger route choice in urban metro network (2019)
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References

  • 2011Smart card data use in public transit: A literature review978 cited
  • 2013Mining smart card data for transit riders’ travel patterns627 cited
  • 2014Behavioural data mining of transit smart card data: A data fusion approach283 cited
  • 2007Measuring transit use variability with smart-card data283 cited
  • 2009Analyzing Multimodal Public Transport Journeys in London with Smart Card Fare Payment Data190 cited
  • 2012Detection of Activities of Public Transport Users by Analyzing Smart Card Data148 cited
  • 2012Spatial-Temporal Daily Frequent Trip Pattern of Public Transport Passengers Using Smart Card Data66 cited
  • 2011Geodemographic analysis and the identification of potential business partnerships enabled by transit smart cards44 cited
  • 2013Bus Dwell Time Estimation and Prediction: A Study Case in Shanghai-China39 cited
  • 2012Estimation of behavioural change of railway passengers using smart card data39 cited
  • 2014Transit passenger segmentation using travel regularity mined from Smart Card transactions data31 cited
  • 2007Modeling Transit Travel Patterns from Location-Stamped Smart Card Data Using a Disaggregate Approach24 cited

Cited by

  • 2020Issues of Development of Smart Transport Assessment Indicators6 cited

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