Estimating on-board passenger comfort in public transport vehicles using incomplete automatic passenger counting data
Estimating on-board passenger comfort in public transport vehicles using incomplete automatic passenger counting data
The prevention of crowding inside buses, trams and trains is an important component of on-board passenger comfort and is central to the provision of good public transport services. In light of the COVID-19 pandemic and the associated significant reduction in public transport patronage and, more importantly, in passenger confidence, the avoidance of crowds by passengers and operators alike becomes even more critical. This is where the provision of information on on-board comfort becomes a necessity. The present study, therefore, proposes a new Kalman filter based estimation scheme for on-board comfort levels, employing historical and current (same-day) non-exhaustive Automatic Passenger Counting data, as well as Automatic Vehicle Locating measurements. The accuracy and reliability of the estimation is, then, evaluated through application to the tramway network of the French city of Nantes. The results suggest that the proposed method is able to deliver good estimation accuracy, both in terms of absolute passenger numbers, but also, more crucially, in terms of on-board comfort Levels of Service.
Roncoli, C.
959c8e30-003d-4965-9b42-84e2a57a23da
Chandakas, E.
ffb2cf84-d3a8-49f7-bd10-9811fe911035
Kaparias, Ioannis
e7767c57-7ac8-48f2-a4c6-6e3cb546a0b7
1 December 2022
Roncoli, C.
959c8e30-003d-4965-9b42-84e2a57a23da
Chandakas, E.
ffb2cf84-d3a8-49f7-bd10-9811fe911035
Kaparias, Ioannis
e7767c57-7ac8-48f2-a4c6-6e3cb546a0b7
Roncoli, C., Chandakas, E. and Kaparias, Ioannis
(2022)
Estimating on-board passenger comfort in public transport vehicles using incomplete automatic passenger counting data.
Transportation Research Part C: Emerging Technologies, 146, [103963].
(doi:10.1016/j.trc.2022.103963).
Abstract
The prevention of crowding inside buses, trams and trains is an important component of on-board passenger comfort and is central to the provision of good public transport services. In light of the COVID-19 pandemic and the associated significant reduction in public transport patronage and, more importantly, in passenger confidence, the avoidance of crowds by passengers and operators alike becomes even more critical. This is where the provision of information on on-board comfort becomes a necessity. The present study, therefore, proposes a new Kalman filter based estimation scheme for on-board comfort levels, employing historical and current (same-day) non-exhaustive Automatic Passenger Counting data, as well as Automatic Vehicle Locating measurements. The accuracy and reliability of the estimation is, then, evaluated through application to the tramway network of the French city of Nantes. The results suggest that the proposed method is able to deliver good estimation accuracy, both in terms of absolute passenger numbers, but also, more crucially, in terms of on-board comfort Levels of Service.
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Accepted/In Press date: 21 November 2022
e-pub ahead of print date: 1 December 2022
Published date: 1 December 2022
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Funding Information:
The authors would like to thank Semitan for supplying the data used in this study, and in particular the ‘‘Direction de la Performance et de l’Innovation’’ for their assistance in analysing the Autumn 2019 Opthor and Ineo datasets. The author Claudio Roncoli also acknowledges the support of the Academy of Finland project ALCOSTO (349327).
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Local EPrints ID: 473186
URI: http://eprints.soton.ac.uk/id/eprint/473186
ISSN: 0968-090X
PURE UUID: e808a467-e249-4da0-b2df-b34a652ef0f6
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Date deposited: 11 Jan 2023 17:57
Last modified: 17 Mar 2024 03:45
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Author:
C. Roncoli
Author:
E. Chandakas
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