IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/halshs-03721297.html
   My bibliography  Save this paper

The Potential of Wi-Fi Data to Estimate Bus Passenger Mobility

Author

Listed:
  • Léa Fabre

    (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique, SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Caroline Bayart

    (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Patrick Bonnel

    (LAET - Laboratoire Aménagement Économie Transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique)

  • Nicolas Mony

Abstract

Using technologies such as Wi-Fi and Bluetooth allows to gather passive mobility data, useful for ensuring the sustainable development of transport infrastructures. The challenge of passive data collection is to be able to identify relevant data. Our research presents interesting solutions for sorting the transmitted signals and reconstructing quality Origin-Destination matrices. Its originality consists not only in comparing the results with those of other data sources, but also in proposing a methodology that can be reproduced. Thanks to a partitioning algorithm, it is possible to automatically distinguish passengers from non-passengers to get transit ridership flow and O-D matrices. The findings show that this algorithm provides concrete and replicable solutions to transport operators for understanding travel demand.

Suggested Citation

  • Léa Fabre & Caroline Bayart & Patrick Bonnel & Nicolas Mony, 2022. "The Potential of Wi-Fi Data to Estimate Bus Passenger Mobility," Working Papers halshs-03721297, HAL.
    • Handle: RePEc:hal:wpaper:halshs-03721297
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03721297
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-03721297/document
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Patrick Bonnel & Caroline Bayart & Brett Smith, 2015. "Workshop Synthesis: Comparing and Combining Survey Modes," Post-Print halshs-01663724, HAL.
    2. Caroline Bayart & Patrick Bonnel, 2012. "Combining web and face-to-face in travel surveys: comparability challenges?," Transportation, Springer, vol. 39(6), pages 1147-1171, November.
    3. Borkowski, Przemysław & Jażdżewska-Gutta, Magdalena & Szmelter-Jarosz, Agnieszka, 2021. "Lockdowned: Everyday mobility changes in response to COVID-19," Journal of Transport Geography, Elsevier, vol. 90(C).
    4. Michele Nitti & Francesca Pinna & Lucia Pintor & Virginia Pilloni & Benedetto Barabino, 2020. "iABACUS: A Wi-Fi-Based Automatic Bus Passenger Counting System," Energies, MDPI, vol. 13(6), pages 1-21, March.
    Full references (including those not matched with items on IDEAS)

    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. Aschauer, Florian & Hössinger, Reinhard & Jara-Diaz, Sergio & Schmid, Basil & Axhausen, Kay & Gerike, Regine, 2021. "Comprehensive data validation of a combined weekly time use and travel survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 66-82.
    2. Caroline Bayart & Patrick Bonnel, 2015. "How to Combine Survey Media (Web, Telephone, Face-to-Face): Lyon and Rhône-alps Case Study," Post-Print halshs-01663683, HAL.
    3. Kim, Suji & Lee, Sujin & Ko, Eunjeong & Jang, Kitae & Yeo, Jiho, 2021. "Changes in car and bus usage amid the COVID-19 pandemic: Relationship with land use and land price," Journal of Transport Geography, Elsevier, vol. 96(C).
    4. Li, Siping & Zhou, Yaoming & Kundu, Tanmoy & Sheu, Jiuh-Biing, 2021. "Spatiotemporal variation of the worldwide air transportation network induced by COVID-19 pandemic in 2020," Transport Policy, Elsevier, vol. 111(C), pages 168-184.
    5. Mourtakos, Vasileios & Mantouka, Eleni G. & Fafoutellis, Panagiotis & Vlahogianni, Eleni I. & Kepaptsoglou, Konstantinos, 2024. "Reconstructing mobility from smartphone data: Empirical evidence of the effects of COVID-19 pandemic crisis on working and leisure," Transport Policy, Elsevier, vol. 146(C), pages 241-254.
    6. Christine Eisenmann & Bastian Chlond & Clotilde Minster & Christian Jödden & Peter Vortisch, 2019. "Assessing the effects of a mixed-mode design in a longitudinal household travel survey," Transportation, Springer, vol. 46(5), pages 1737-1753, October.
    7. Bayart, Caroline & Bonnel, Patrick & Havet, Nathalie, 2018. "Daily (im)mobility behaviours in France: An application of hurdle models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 456-467.
    8. Wai Peng Wong & Muhammad Fahad Anwar & Keng Lin Soh, 2024. "Transportation 4.0 in supply chain management: State-of-the-art and future directions towards 5.0 in the transportation sector," Operations Management Research, Springer, vol. 17(2), pages 683-710, June.
    9. Kahalimoghadam, Masoud & Thompson, Russell G. & Rajabifard, Abbas, 2024. "Determining the number and location of micro-consolidation centres as a solution to growing e-commerce demand," Journal of Transport Geography, Elsevier, vol. 117(C).
    10. Basa-Martinez, Diana Denise F. & Cabrera, Janet Y. & Dionaldo, LA G. & Orillo, Jonathan Gavino R. & Ramos, Paul John M. & Ocampo, Lanndon A., 2018. "An exploration of a respondent pre-qualifying framework to increase response rates in social media initiated online surveys," Australasian marketing journal, Elsevier, vol. 26(3), pages 239-261.
    11. Semple, Torran & Fonzone, Achille & Fountas, Grigorios & Downey, Lucy, 2023. "An empirical analysis of the factors influencing Scottish residents’ compliance with COVID-19 travel restrictions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    12. Hakan Yilmazkuday, 2020. "Stay-at-Home Works to Fight Against COVID-19: International Evidence from Google Mobility Data," Working Papers 2008, Florida International University, Department of Economics.
    13. Benedetto Barabino & Mauro Coni & Massimo Francesco & Andrea Obino & Roberto Ventura, 2024. "Origin–destination matrices from smartphone apps for bus networks," Public Transport, Springer, vol. 16(2), pages 505-549, June.
    14. Marta Borowska-Stefańska & Michał Kowalski & Paulina Kurzyk & Alireza Sahebgharani & Szymon Wiśniewski, 2022. "Spatiotemporal Changeability of the Load of the Urban Road Transport System under Permanent and Short-Term Legal and Administrative Retail Restrictions," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    15. Bohman, Helena & Ryan, Jean & Stjernborg, Vanessa & Nilsson, Désirée, 2021. "A study of changes in everyday mobility during the Covid-19 pandemic: As perceived by people living in Malmö, Sweden," Transport Policy, Elsevier, vol. 106(C), pages 109-119.
    16. Dirzka, Christopher & Acciaro, Michele, 2022. "Global shipping network dynamics during the COVID-19 pandemic's initial phases," Journal of Transport Geography, Elsevier, vol. 99(C).
    17. Colaço, Rui & Kappler, Laísa Braga & de Abreu e Silva, João, 2024. "Pandemic immobilities and consequences for commuting: Implications for mobility of COVID-19 mandatory telecommuting," Journal of Transport Geography, Elsevier, vol. 114(C).
    18. Nicholas S. Caros & Jinhua Zhao, 2022. "Preparing urban mobility for the future of work," Papers 2201.01321, arXiv.org.
    19. Li, Meng-Hao & Haynes, Kingsley & Kulkarni, Rajendra & Siddique, Abu Bakkar, 2022. "Determinants of voluntary compliance: COVID-19 mitigation," Social Science & Medicine, Elsevier, vol. 310(C).
    20. Liu, Anyu & Kim, Yoo Ri & O'Connell, John Frankie, 2021. "COVID-19 and the aviation industry: The interrelationship between the spread of the COVID-19 pandemic and the frequency of flights on the EU market," Annals of Tourism Research, Elsevier, vol. 91(C).

    More about this item

    Keywords

    Travel behavior; passive tracking; data clustering; Wi-Fi/Bluetooth sensors; trajectory reconstruction; mobile devices data; data quality; Working Papers du LAET;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:wpaper:halshs-03721297. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.