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Crowding cost estimation with large scale smart card and vehicle location data

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  1. Singh, Jyotsna & Homem de Almeida Correia, Gonçalo & van Wee, Bert & Barbour, Natalia, 2023. "Change in departure time for a train trip to avoid crowding during the COVID-19 pandemic: A latent class study in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
  2. Bouscasse, Hélène & de Lapparent, Matthieu, 2019. "Perceived comfort and values of travel time savings in the Rhône-Alpes Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 370-387.
  3. Rossetti, Tomás & Daziano, Ricardo A., 2024. "Crowding multipliers on shared transportation in New York City: The effects of COVID-19 and implications for a sustainable future," Transport Policy, Elsevier, vol. 145(C), pages 224-236.
  4. Varghese, Varun & Moniruzzaman, Md. & Chikaraishi, Makoto, 2023. "Environmental sustainability or equity in welfare? Analysing passenger flows of a mass rapid transit system with heterogeneous demand," Research in Transportation Economics, Elsevier, vol. 97(C).
  5. Hörcher, Daniel & Tirachini, Alejandro, 2021. "A review of public transport economics," Economics of Transportation, Elsevier, vol. 25(C).
  6. Svanberg , Lisa & Pyddoke, Roger, 2020. "Policies for on-board crowding in public transportation : a literature review," Working Papers 2020:6, Swedish National Road & Transport Research Institute (VTI).
  7. Yu, Liping & Liu, Huiran & Fang, Zhiming & Ye, Rui & Huang, Zhongyi & You, Yayun, 2023. "A new approach on passenger flow assignment with multi-connected agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
  8. Davis, Lucas W., 2021. "Estimating the price elasticity of demand for subways: Evidence from Mexico," Regional Science and Urban Economics, Elsevier, vol. 87(C).
  9. Aghabayk, Kayvan & Esmailpour, Javad & Shiwakoti, Nirajan, 2021. "Effects of COVID-19 on rail passengers’ crowding perceptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 186-202.
  10. Hörcher, Daniel & Graham, Daniel J., 2020. "MaaS economics: Should we fight car ownership with subscriptions to alternative modes?," Economics of Transportation, Elsevier, vol. 22(C).
  11. Tirachini, Alejandro & Hurtubia, Ricardo & Dekker, Thijs & Daziano, Ricardo A., 2017. "Estimation of crowding discomfort in public transport: Results from Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 311-326.
  12. Arbex, Renato & Cunha, Claudio B., 2020. "Estimating the influence of crowding and travel time variability on accessibility to jobs in a large public transport network using smart card big data," Journal of Transport Geography, Elsevier, vol. 85(C).
  13. Luan, Xiaojie & Corman, Francesco, 2022. "Passenger-oriented traffic control for rail networks: An optimization model considering crowding effects on passenger choices and train operations," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 239-272.
  14. Paudel, Jayash, 2021. "Bus ridership and service reliability: The case of public transportation in Western Massachusetts," Transport Policy, Elsevier, vol. 100(C), pages 98-107.
  15. Zhang, Qian & Liu, Xiaoxiao & Spurgeon, Sarah & Yu, Dingli, 2021. "A two-layer modelling framework for predicting passenger flow on trains: A case study of London underground trains," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 119-139.
  16. Anne Halvorsen & Haris N. Koutsopoulos & Zhenliang Ma & Jinhua Zhao, 2020. "Demand management of congested public transport systems: a conceptual framework and application using smart card data," Transportation, Springer, vol. 47(5), pages 2337-2365, October.
  17. Ingvardson, Jesper Bláfoss & Thorhauge, Mikkel & Nielsen, Otto Anker & Eltved, Morten, 2024. "Public transport route choice modelling: Reducing estimation bias when using smart card data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
  18. Weiyan Mu & Xin Wang & Chunya Li & Shifeng Xiong, 2023. "Dynamic Modeling for Metro Passenger Flows on Congested Transfer Routes," Mathematics, MDPI, vol. 11(6), pages 1-20, March.
  19. Prateek Bansal & Daniel Horcher & Daniel J. Graham, 2020. "A Dynamic Choice Model with Heterogeneous Decision Rules: Application in Estimating the User Cost of Rail Crowding," Papers 2007.03682, arXiv.org.
  20. Hörcher, Daniel & Graham, Daniel J. & Anderson, Richard J., 2018. "The economics of seat provision in public transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 277-292.
  21. Sanmay Shelat & Oded Cats & Sander van Cranenburgh, 2021. "Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands," Papers 2104.10973, arXiv.org, revised Apr 2022.
  22. Jinwon Kim & Jucheol Moon, 2022. "Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data," Working Papers 2201, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
  23. Bansal, Prateek & Hurtubia, Ricardo & Tirachini, Alejandro & Daziano, Ricardo A., 2019. "Flexible estimates of heterogeneity in crowding valuation in the New York City subway," Journal of choice modelling, Elsevier, vol. 31(C), pages 124-140.
  24. Yu, Chao & Li, Haiying & Xu, Xinyue & Liu, Jun, 2020. "Data-driven approach for solving the route choice problem with traveling backward behavior in congested metro systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
  25. Hong En Tan & De Wen Soh & Yong Sheng Soh & Muhamad Azfar Ramli, 2021. "Derivation of train arrival timings through correlations from individual passenger farecard data," Transportation, Springer, vol. 48(6), pages 3181-3205, December.
  26. Abderrahman Ait-Ali & Jonas Eliasson, 2022. "The value of additional data for public transport origin–destination matrix estimation," Public Transport, Springer, vol. 14(2), pages 419-439, June.
  27. Jenelius, Erik, 2018. "Public transport experienced service reliability: Integrating travel time and travel conditions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 275-291.
  28. Taoyuan Yang & Peng Zhao & Xiangming Yao, 2020. "A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules," Sustainability, MDPI, vol. 12(6), pages 1-13, March.
  29. Junya Kumagai & Mihoko Wakamatsu & Shunsuke Managi, 2021. "Do commuters adapt to in-vehicle crowding on trains?," Transportation, Springer, vol. 48(5), pages 2357-2399, October.
  30. Haywood, Luke & Koning, Martin & Prud'homme, Remy, 2018. "The economic cost of subway congestion: Estimates from Paris," Economics of Transportation, Elsevier, vol. 14(C), pages 1-8.
  31. Hänseler, Flurin S. & van den Heuvel, Jeroen P.A. & Cats, Oded & Daamen, Winnie & Hoogendoorn, Serge P., 2020. "A passenger-pedestrian model to assess platform and train usage from automated data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 948-968.
  32. Menno Yap & Oded Cats, 2021. "Predicting disruptions and their passenger delay impacts for public transport stops," Transportation, Springer, vol. 48(4), pages 1703-1731, August.
  33. Yap, Menno & Cats, Oded, 2021. "Taking the path less travelled: Valuation of denied boarding in crowded public transport systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 1-13.
  34. Mu Lin & Zhengdong Huang & Tianhong Zhao & Ying Zhang & Heyi Wei, 2022. "Spatiotemporal Evolution of Travel Pattern Using Smart Card Data," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
  35. Nan Zhang & Daniel J. Graham & Daniel Hörcher & Prateek Bansal, 2021. "A causal inference approach to measure the vulnerability of urban metro systems," Transportation, Springer, vol. 48(6), pages 3269-3300, December.
  36. Luigi Moccia & Duncan W. Allen & Eric C. Bruun, 2018. "A technology selection and design model of a semi-rapid transit line," Public Transport, Springer, vol. 10(3), pages 455-497, December.
  37. Xuto, Praj & Anderson, Richard J. & Graham, Daniel J. & Hörcher, Daniel, 2021. "Optimal infrastructure reinvestment in urban rail systems: A dynamic supply optimisation approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 251-268.
  38. Ait Ali, Abderrahman & Eliasson, Jonas & Warg, Jennifer, 2022. "Are commuter train timetables consistent with passengers’ valuations of waiting times and in-vehicle crowding?," Transport Policy, Elsevier, vol. 116(C), pages 188-198.
  39. Daniel Hörcher & Daniel J. Graham, 2021. "The Gini index of demand imbalances in public transport," Transportation, Springer, vol. 48(5), pages 2521-2544, October.
  40. Hörcher, Daniel & De Borger, Bruno & Seifu, Woubit & Graham, Daniel J., 2020. "Public transport provision under agglomeration economies," Regional Science and Urban Economics, Elsevier, vol. 81(C).
  41. Anupriya, & Graham, Daniel J. & Hörcher, Daniel & Anderson, Richard J. & Bansal, Prateek, 2020. "Quantifying the ex-post causal impact of differential pricing on commuter trip scheduling in Hong Kong," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 16-34.
  42. Moccia, Luigi & Giallombardo, Giovanni & Laporte, Gilbert, 2017. "Models for technology choice in a transit corridor with elastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 733-756.
  43. Caterina Malandri & Luca Mantecchini & Filippo Paganelli & Maria Nadia Postorino, 2021. "Public Transport Network Vulnerability and Delay Distribution among Travelers," Sustainability, MDPI, vol. 13(16), pages 1-14, August.
  44. Márquez, Luis & Alfonso A, Julieth V. & Poveda, Juan C., 2019. "In-vehicle crowding: Integrating tangible attributes, attitudes, and perceptions in a choice context between BRT and metro," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 452-465.
  45. Zhu, Yiwen & Koutsopoulos, Haris N. & Wilson, Nigel H.M., 2017. "A probabilistic Passenger-to-Train Assignment Model based on automated data," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 522-542.
  46. Anupriya, & Graham, Daniel J. & Bansal, Prateek & Hörcher, Daniel & Anderson, Richard, 2023. "Optimal congestion control strategies for near-capacity urban metros: Informing intervention via fundamental diagrams," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
  47. Chen, Xin & Jiang, Yu & Bláfoss Ingvardson, Jesper & Luo, Xia & Anker Nielsen, Otto, 2023. "I can board, but I’d rather wait: Active boarding delay choice behaviour analysis using smart card data in metro systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
  48. Shelat, Sanmay & Cats, Oded & van Cranenburgh, Sander, 2022. "Traveller behaviour in public transport in the early stages of the COVID-19 pandemic in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 357-371.
  49. Hörcher, Daniel & Graham, Daniel J., 2018. "Demand imbalances and multi-period public transport supply," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 106-126.
  50. Godwin Yeboah & Caitlin D. Cottrill & John D. Nelson & David Corsar & Milan Markovic & Peter Edwards, 2019. "Understanding factors influencing public transport passengers’ pre-travel information-seeking behaviour," Public Transport, Springer, vol. 11(1), pages 135-158, June.
  51. Prateek Bansal & Daniel Hörcher & Daniel J. Graham, 2022. "A dynamic choice model to estimate the user cost of crowding with large‐scale transit data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(2), pages 615-639, April.
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