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

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  • 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, LSAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)

  • Caroline Bayart

    (LSAF - 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-03721297v1
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    References listed on IDEAS

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