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Deep-learning-based model for prediction of crowding in a public transit system
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Deep-learning-based model for prediction of crowding in a public transit system (2024)Deep-learning-based model for prediction …Robustness and disturbances in public transport (2022)Robustness and disturbances i…Effects of COVID-19 on rail passengers’ crowding perceptions (2021)Effects of COVID-19 on rail p…A paradigm shift in urban mobility: Policy insights from travel before and after COVID-19 to seize the opportunity (2021)A paradigm shift in urban mob…Fare evasion in public transport systems: a review of the literature (2020)Fare evasion in public transp…Public transport trip purpose inference using smart card fare data (2018)Public transport trip purpose…Public Transport Planning with Smart Card Data (2017)Public Transport Planning wit…Estimation of crowding discomfort in public transport: Results from Santiago de Chile (2017)Estimation of crowding discom…Deep‐learning architecture to forecast destinations of bus passengers from entry‐only smart‐card data (2017)Deep‐learning architecture to…Headway-based bus bunching prediction using transit smart card data (2016)Headway-based bus bunching pr…Detecting home location and trip purposes for cardholders by mining smart card transaction data in Beijing subway (2016)Detecting home location and t…Use of Smart Card Fare Data to Estimate Public Transport Origin–Destination Matrix (2015)Use of Smart Card Fare Data t…Round-Based Public Transit Routing (2014)Round-Based Public Transit Ro…Mining smart card data for transit riders’ travel patterns (2013)Mining smart card data for tr…Crowding in Public Transport: A Review of Objective and Subjective Measures (2013)Crowding in Public Transport:…Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand (2013)Crowding in public transport …Measuring transit use variability with smart-card data (2007)Measuring transit use variabi…Smart card data use in public transit: A literature review (2011)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)Discrete Choice Methods with Simulation (2001)Discrete Choice Methods with Simulation (2003)Applied choice analysis a primer (2005)Crowding cost estimation with large scale smart card and vehicle location data (2016)Travel satisfaction with public transport: Determinants, user classes, regional disparities and their evolution (2016)A Review of Public Transport Economics (2020)Service quality––developing a service quality index in the provision of commercial bus contracts (2003)Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal (2011)Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding (2014)Cumulative prospect theory coupled with multi-attribute decision making for modeling travel behavior (2021)Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands (2022)Efficient models for timetable information in public transportation systems (2007)Evidence-Based Transit and Land Use Sketch Planning Using Interactive Accessibility Methods on Combined Schedule and Headway-Based Networks (2017)Quantifying multi-modal public transit accessibility for large metropolitan areas: a time-dependent reliability modeling approach (2018)Route guidance ranking procedures with human perception consideration for personalized public transport service (2020)Observing the rhythms of daily life: A six-week travel diary (2002)Introduction: Habitual travel choice (2003)The potential of public transport smart card data (2005)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)Discovering the spatio-temporal impacts of built environment on metro ridership using smart card data (2019)A latent class model for discrete choice analysis: contrasts with mixed logit (2003)The underlying effect of public transport reliability on users’ satisfaction (2019)Public transport accessibility accounting for level of service and competition for urban opportunities: An equity analysis for education in Santiago de Chile (2020)The role of habit and the built environment in the willingness to commute by bicycle (2020)Transit capacity and quality of service manual (2003)Origin–destination trips by purpose and time of day inferred from mobile phone data (2015)Data-driven activity scheduler for agent-based mobility models (2018)Big data in public transportation: a review of sources and methods (2019)Emerging Big Data Sources for Public Transport Planning: A Systematic Review on Current State of Art and Future Research Directions (2019)A Structural Model of Peak-Period Congestion: A Traffic Bottleneck with Elastic Demand (1993)How COVID-19 and the Dutch ‘intelligent lockdown’ change activities, work and travel behaviour: Evidence from longitudinal data in the Netherlands (2020)Psychosocial impact of COVID-19 (2020)The impact of COVID-19 on future public transport use in Scotland (2022)The Long-Term effects of COVID-19 on travel behavior in the United States: A panel study on work from home, mode choice, online shopping, and air travel (2022)Progress and prospects in planning: A bibliometric review of literature in Urban Studies and Regional and Urban Planning, 1956–2022 (2023)Job-worker spatial dynamics in Beijing: Insights from Smart Card Data (2018)Discovering latent activity patterns from transit smart card data: A spatiotemporal topic model (2020)Quantifying the Causal Effect of Individual Mobility on Health Status in Urban Space (2021)Smart Card Data Mining of Public Transport Destination: A Literature Review (2018)A Review of Big Data Applications in Urban Transit Systems (2020)
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References

  • 2013Mining smart card data for transit riders’ travel patterns606 cited
  • 2013Crowding in public transport systems: Effects on users, operation and implications for the estimation of demand385 cited
  • 2007Measuring transit use variability with smart-card data271 cited
  • 2014Round-Based Public Transit Routing168 cited
  • 2021A paradigm shift in urban mobility: Policy insights from travel before and after COVID-19 to seize the opportunity162 cited
  • 2018Public transport trip purpose inference using smart card fare data160 cited
  • 2017Estimation of crowding discomfort in public transport: Results from Santiago de Chile152 cited
  • 2013Crowding in Public Transport: A Review of Objective and Subjective Measures149 cited
  • 2015Use of Smart Card Fare Data to Estimate Public Transport Origin–Destination Matrix108 cited
  • 2016Detecting home location and trip purposes for cardholders by mining smart card transaction data in Beijing subway84 cited
  • 2020Fare evasion in public transport systems: a review of the literature84 cited
  • 2016Headway-based bus bunching prediction using transit smart card data80 cited
  • 2022Robustness and disturbances in public transport80 cited
  • 2021Effects of COVID-19 on rail passengers’ crowding perceptions77 cited

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2017
Deep‐learning architecture to forecast destinations of bus passengers from entry‐only smart‐card data
77 cited
  • 2017Public Transport Planning with Smart Card Data66 cited
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