Long Enough But Not Too Long : A Posteriori Determination of the Dwell Time Margins from High-Resolution Passenger Flow Data
Baali, Mehdi ; Kuipers, Ruben LU ; Coulaud, Rémi ; Buisson, Christine and Palmqvist, Carl William LU
(2025)
In Data Science for Transportation
7(2).
- Abstract
Dwell time is crucial for railway operations, for example, 20% of the total travel time in a mass transit context in the Paris region. With this, it is also a source of delays due to its variability. One way to ensure the robustness of a timetable is to add margins as buffer time that can be consumed to absorb short delays. Much work has been done on run time margins, but dwell time margins received little attention, except for a few heuristics. This paper aims to provide a novel method to estimate dwell time margins. To do so, we introduce the notion of tight dwell time as the duration of a continuous alighting and boarding flow with the addition of the technical times and compute it from high-resolution passenger flow data. Then, we... (More)
Dwell time is crucial for railway operations, for example, 20% of the total travel time in a mass transit context in the Paris region. With this, it is also a source of delays due to its variability. One way to ensure the robustness of a timetable is to add margins as buffer time that can be consumed to absorb short delays. Much work has been done on run time margins, but dwell time margins received little attention, except for a few heuristics. This paper aims to provide a novel method to estimate dwell time margins. To do so, we introduce the notion of tight dwell time as the duration of a continuous alighting and boarding flow with the addition of the technical times and compute it from high-resolution passenger flow data. Then, we propose two novel methods: the cluster method and the quantile method to estimate it. Given the access to this data, the methods enable the estimation of the tight dwell time for all the stops while existing heuristics are limited to late trains and/or few passengers. Our developed methods highlight the propensity of existing heuristics to underestimate dwell time margins. A posteriori, the estimation of dwell time margins thanks to the computed tight dwell time would help design future timetables.
(Less)
- author
- Baali, Mehdi
; Kuipers, Ruben
LU
; Coulaud, Rémi
; Buisson, Christine
and Palmqvist, Carl William
LU
- organization
- publishing date
- 2025-08
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Alighting and boarding time, Dwell time, Margins, Passenger flow data, Railway
- in
- Data Science for Transportation
- volume
- 7
- issue
- 2
- article number
- 7
- publisher
- Springer
- external identifiers
-
- scopus:105003889173
- ISSN
- 2948-135X
- DOI
- 10.1007/s42421-025-00121-9
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.
- id
- 3a0d6f35-f5cb-4049-8289-2ec0c4c8c235
- date added to LUP
- 2025-05-19 09:55:00
- date last changed
- 2025-06-02 10:14:41
@article{3a0d6f35-f5cb-4049-8289-2ec0c4c8c235,
abstract = {{<p>Dwell time is crucial for railway operations, for example, 20% of the total travel time in a mass transit context in the Paris region. With this, it is also a source of delays due to its variability. One way to ensure the robustness of a timetable is to add margins as buffer time that can be consumed to absorb short delays. Much work has been done on run time margins, but dwell time margins received little attention, except for a few heuristics. This paper aims to provide a novel method to estimate dwell time margins. To do so, we introduce the notion of tight dwell time as the duration of a continuous alighting and boarding flow with the addition of the technical times and compute it from high-resolution passenger flow data. Then, we propose two novel methods: the cluster method and the quantile method to estimate it. Given the access to this data, the methods enable the estimation of the tight dwell time for all the stops while existing heuristics are limited to late trains and/or few passengers. Our developed methods highlight the propensity of existing heuristics to underestimate dwell time margins. A posteriori, the estimation of dwell time margins thanks to the computed tight dwell time would help design future timetables.</p>}},
author = {{Baali, Mehdi and Kuipers, Ruben and Coulaud, Rémi and Buisson, Christine and Palmqvist, Carl William}},
issn = {{2948-135X}},
keywords = {{Alighting and boarding time; Dwell time; Margins; Passenger flow data; Railway}},
language = {{eng}},
number = {{2}},
publisher = {{Springer}},
series = {{Data Science for Transportation}},
title = {{Long Enough But Not Too Long : A Posteriori Determination of the Dwell Time Margins from High-Resolution Passenger Flow Data}},
url = {{http://dx.doi.org/10.1007/s42421-025-00121-9}},
doi = {{10.1007/s42421-025-00121-9}},
volume = {{7}},
year = {{2025}},
}