Predicting and mitigating small fluctuations in station dwell times
Predicting and mitigating small fluctuations in station dwell times
On busy railway networks, exceeding station dwell times by only a few seconds can adversely affect overall network performance. However, while these performance impacts are well known, the causes of small dwell time perturbations are not widely understood (or are not widely communicated at an operational level) and exhibit a high level of spatial and temporal variation. A lack of information and understanding makes it difficult to implement effective mitigation measures to reduce the occurrence and impact of such delays. For this paper On Train Monitoring Recorder (OTMR) data were obtained for a large number of services over a 14month period, which included the wheel stop and wheel start timings associated with station stops at a 1 second resolution. These were combined with other relevant data sources in order to investigate small fluctuations in station dwell time. An interface for communicating these variations to railway operating staff was developed, along with models to predict future dwell time fluctuations, potentially enabling mitigation measures to be implemented.
Delay, Modelling, Station dwell
Pritchard, James
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Sadler, Jason
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Blainey, Simon
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Waldock, Ian
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Austin, Jeremy RN
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June 2021
Pritchard, James
6eabbdbc-385b-4636-9bd5-c0ac239f2351
Sadler, Jason
857a8e67-cfe3-489b-9f3a-3ccbc0d3930f
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Waldock, Ian
fb59d4fd-2861-4ed6-b987-1d35722e81b3
Austin, Jeremy RN
569a0f9b-8129-4649-93f2-b2f09516f53a
Pritchard, James, Sadler, Jason, Blainey, Simon, Waldock, Ian and Austin, Jeremy RN
(2021)
Predicting and mitigating small fluctuations in station dwell times.
Journal of Rail Transport Planning & Management, 18, [100249].
(doi:10.1016/j.jrtpm.2021.100249).
Abstract
On busy railway networks, exceeding station dwell times by only a few seconds can adversely affect overall network performance. However, while these performance impacts are well known, the causes of small dwell time perturbations are not widely understood (or are not widely communicated at an operational level) and exhibit a high level of spatial and temporal variation. A lack of information and understanding makes it difficult to implement effective mitigation measures to reduce the occurrence and impact of such delays. For this paper On Train Monitoring Recorder (OTMR) data were obtained for a large number of services over a 14month period, which included the wheel stop and wheel start timings associated with station stops at a 1 second resolution. These were combined with other relevant data sources in order to investigate small fluctuations in station dwell time. An interface for communicating these variations to railway operating staff was developed, along with models to predict future dwell time fluctuations, potentially enabling mitigation measures to be implemented.
Text
DwellTime
- Accepted Manuscript
More information
Accepted/In Press date: 16 March 2021
e-pub ahead of print date: 27 May 2021
Published date: June 2021
Additional Information:
Funding Information:
This research was funded by RSSB as part of its Data Sandbox: Improving Network Performance competition. It was supported by rail industry partners, including South Western Railway , who provided data and operational insights and Network Rail who provided access to their Network Model.
Funding Information:
This research was funded by RSSB as part of its Data Sandbox: Improving Network Performance competition. It was supported by rail industry partners, including South Western Railway, who provided data and operational insights and Network Rail who provided access to their Network Model.
Publisher Copyright:
© 2021 Elsevier Ltd
Keywords:
Delay, Modelling, Station dwell
Identifiers
Local EPrints ID: 449740
URI: http://eprints.soton.ac.uk/id/eprint/449740
ISSN: 2210-9706
PURE UUID: 5451e081-868c-4561-b2d7-1ebbc001ffe2
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Date deposited: 15 Jun 2021 16:32
Last modified: 17 Mar 2024 06:27
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Author:
James Pritchard
Author:
Jeremy RN Austin
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