IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v165y2022icp267-284.html

Inferring origin and destination zones of transit trips through fusion of smart card transactions, travel surveys, and land-use data

Author

Listed:
  • Hossain, Sanjana
  • Habib, Khandker Nurul

Abstract

This paper presents a data fusion method to infer the origin and destination zones of transit trips from smart card data. The fusion framework has disaggregate mixed multinomial logit models at its core that predict the most probable origin and destination zones of individual transit trips using smart card transaction records, land use data, and transit system characteristics. The logit models are estimated using revealed trip origin and destination responses from a travel survey that are augmented by land use and transit system data to provide contexts about the zones' trip generation and attraction potentials. For empirical analysis, the methodology is applied to the smart card system of the Greater Toronto and Hamilton Area. Specifically, it is tested under different system configurations (tap-on-only and tap-on-and-off) and for networks with substantial shares of automobile and walk access/egress. When applied to transit trips constructed from the smart card transactions, the estimated models successfully capture the spatial distribution of trip origin and destination at the traffic analysis zone level. The empirical analysis also demonstrates that the proposed fusion method can be appropriately used to reconcile information provided by transit smart card and travel surveys to generate up-to-date transit demand data necessary for public transport planning and operations.

Suggested Citation

  • Hossain, Sanjana & Habib, Khandker Nurul, 2022. "Inferring origin and destination zones of transit trips through fusion of smart card transactions, travel surveys, and land-use data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 267-284.
    • Handle: RePEc:eee:transa:v:165:y:2022:i:c:p:267-284
    DOI: 10.1016/j.tra.2022.09.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856422002452
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2022.09.010?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Daly, Andrew, 1982. "Estimating choice models containing attraction variables," Transportation Research Part B: Methodological, Elsevier, vol. 16(1), pages 5-15, February.
    2. Egu, Oscar & Bonnel, Patrick, 2020. "How comparable are origin-destination matrices estimated from automatic fare collection, origin-destination surveys and household travel survey? An empirical investigation in Lyon," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 267-282.
    3. Tamblay, Sebastián & Galilea, Patricia & Iglesias, Paula & Raveau, Sebastián & Muñoz, Juan Carlos, 2016. "A zonal inference model based on observed smart-card transactions for Santiago de Chile," Transportation Research Part A: Policy and Practice, Elsevier, vol. 84(C), pages 44-54.
    4. Guevara, C. Angelo & Ben-Akiva, Moshe E., 2013. "Sampling of alternatives in Logit Mixture models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 185-198.
    5. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    6. Amaya, Margarita & Cruzat, Ramón & Munizaga, Marcela A., 2018. "Estimating the residence zone of frequent public transport users to make travel pattern and time use analysis," Journal of Transport Geography, Elsevier, vol. 66(C), pages 330-339.
    7. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mabit, Stefan E., 2026. "Mixed logit applications in travel behaviour research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 203(C).
    2. Shi, Linchang & Yang, Jiayu & Lee, Jaeyoung Jay & Bai, Jun & Ryu, Ingon & Choi, Keechoo, 2024. "Spatial-temporal identification of commuters using trip chain data from non-motorized mode incentive program and public transportation," Journal of Transport Geography, Elsevier, vol. 117(C).
    3. Feng, Xuan & Jia, Ning & Su, Xiaohan & Adams, Matthew D. & Deng, Yongqi & Ling, Shuai, 2025. "Assessing the applicability of the 15-minute city: Insights from a spatial accessibility perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 199(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. O'Dell, Dallas & Contu, Davide & Shreedhar, Ganga, 2025. "Public support for degrowth policies and sufficiency behaviours in the United States: a discrete choice experiment," LSE Research Online Documents on Economics 126084, London School of Economics and Political Science, LSE Library.
    2. Bina, Justin D. & Tonsor, Glynn T. & Richards, Timothy J., 2026. "GLP-1 use and protein demand," Food Policy, Elsevier, vol. 138(C).
    3. Tiwari, Sapan & Jafari, Afshin & Pemberton, Steve & Ziemke, Dominik, 2026. "Behaviourally informed bicycle route assignment for activity-based and agent-based travel demand modelling," SocArXiv kt94s_v1, Center for Open Science.
    4. Tsoleridis, Panagiotis & Choudhury, Charisma F. & Hess, Stephane, 2022. "Utilising activity space concepts to sampling of alternatives for mode and destination choice modelling of discretionary activities," Journal of choice modelling, Elsevier, vol. 42(C).
    5. Isler, Cassiano Augusto & Blumenfeld, Marcelo & Caldeira, Gabriel Pereira & Roberts, Clive, 2024. "Long-Distance railway mode choice in Brazil: Evidence from a discrete choice experiment," Research in Transportation Economics, Elsevier, vol. 104(C).
    6. Su, Jie & Gasparatos, Alexandros, 2024. "Assessing the heterogeneity of public acceptability for mangrove restoration through a choice experiment," Ecological Economics, Elsevier, vol. 218(C).
    7. Rolfe, John & Carnell, Paul & Marine, Sabiha & Whiteoak, Kym & Zilleruelo, Rodrigo & Wartman, Melissa, 2026. "Valuing coastal wetland restoration in Australia with discrete choice experiments," Ecological Economics, Elsevier, vol. 239(C).
    8. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    9. Li, David C. & Beck, Matthew John & Merkert, Rico, 2026. "Willingness to pay for voluntary airline carbon offsets and sustainable aviation fuel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 204(C).
    10. Fabian Bastin & Cinzia Cirillo & Philippe L. Toint, 2010. "Estimating Nonparametric Random Utility Models with an Application to the Value of Time in Heterogeneous Populations," Transportation Science, INFORMS, vol. 44(4), pages 537-549, November.
    11. Masiero, Lorenzo & Hrankai, Richard, 2022. "Modeling tourist accessibility to peripheral attractions," Annals of Tourism Research, Elsevier, vol. 92(C).
    12. Lehmann, Nico & Sloot, Daniel & Ardone, Armin & Fichtner, Wolf, 2021. "The limited potential of regional electricity marketing – Results from two discrete choice experiments in Germany," Energy Economics, Elsevier, vol. 100(C).
    13. Poudel, Niranjan & Singleton, Patrick A., 2024. "Willingness to pay for changes in travel time and work time: A stated choice experiment of US commuters," Research in Transportation Economics, Elsevier, vol. 103(C).
    14. Darnell Holt & Peter Slade & Jill Hobbs, 2024. "Do consumers care about clean labels? Willingness to pay for simple ingredient lists and front‐of‐package labels on beef and plant‐based burgers," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 72(1), pages 5-21, March.
    15. Bronnmann, Julia & Requate, Till & Steinbrunner, Philipp, 2026. "Unconscious status and car consumption: social comparison effects in a discrete choice experiment," Transportation Research Part A: Policy and Practice, Elsevier, vol. 205(C).
    16. Alice M. Ellyson & Avanti Adhia & Emily Kroshus & Davene R. Wright, 2023. "Student-Athlete Preferences for Sexual Violence Reporting: A Discrete Choice Experiment," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 16(1), pages 77-88, January.
    17. Tsoleridis, Panagiotis & Choudhury, Charisma F. & Hess, Stephane, 2023. "Probabilistic choice set formation incorporating activity spaces into the context of mode and destination choice modelling," Journal of Transport Geography, Elsevier, vol. 108(C).
    18. von Haefen, Roger H. & Domanski, Adam, 2018. "Estimation and welfare analysis from mixed logit models with large choice sets," Journal of Environmental Economics and Management, Elsevier, vol. 90(C), pages 101-118.
    19. Hangjian Wu & Emmanouil Mentzakis & Marije Schaafsma, 2022. "Exploring Different Assumptions about Outcome-Related Risk Perceptions in Discrete Choice Experiments," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 81(3), pages 531-572, March.
    20. Melinda Matyas & Maria Kamargianni, 2019. "Survey design for exploring demand for Mobility as a Service plans," Transportation, Springer, vol. 46(5), pages 1525-1558, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:165:y:2022:i:c:p:267-284. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.