Bayesian Estimation of Passenger Boardings at Bus Stops Using Wi-Fi Probe Requests
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 6
Abstract
The estimation of the number of passenger boardings at every bus stop along an itinerary was solved using a Bayesian method. The method employs probability distributions of Wi-Fi probe requests. Any available technique capable of uniquely identifying probe requests made by onboard Wi-Fi devices can be used for obtaining the samples needed for the estimation. Probability distributions of time intervals between consecutive probe requests provide the information needed for generating the probability density function of boarding amounts at each stop. A case study of synthetic probe requests randomly generated for a bus line comprised of 17 stops indicated the adequacy of the method. Its efficacy increases with the grouping of nearby stops in boarding zones. It is straightforward to modify the method for the estimation of alightings, origin–destination matrixes, and bus loads.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
Diego Benites Paradeda was supported with scholarships from The National Council for Scientific and Technological Development (CNPq) and Coordination for the Improvement of Higher Education Personnel (CAPES). Werner Kraus Junior and Rodrigo Castelan Carlson were partially supported by The National Council for Scientific and Technological Development (CNPq) (Grants 312205/2017-1 and 304555/2020-7, respectively) and by the Coordination for the Improvement of Higher Education Personnel (CAPES) (Grant 48180211991/PROJ-CAPESPRINT1039611P).
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Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 6 • June 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Aug 31, 2022
Accepted: Feb 8, 2023
Published online: Apr 5, 2023
Published in print: Jun 1, 2023
Discussion open until: Sep 5, 2023
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