An automated online tool to forecast demand for new railway stations and analyse potential abstraction effects
An automated online tool to forecast demand for new railway stations and analyse potential abstraction effects
A national trip end model to forecast demand for new local railway stations in Great Britain has been developed and implemented as an automated hosted tool on the Data and Analytics Facility for National Infrastructure (DAFNI). This paper presentation describes the novel characteristics of the underlying model, explains how it has been realised on DAFNI, and incorporates a live demonstration of the tool’s web interface.
The underlying trip end model was calibrated on all existing local stations in mainland GB, and is unique in its scale, adoption of a high spatial resolution zoning system (trip generation is assessed for every postcode), and the incorporation of a station choice model. The latter allows probability-based station catchments to be defined, accounting for competition between stations and enabling the assessment of abstraction effects on existing stations. Testing of the model found that it produced more accurate demand forecasts than methods used during the scheme appraisal process for several recently opened stations and a new line. The model has already been used to produce demand forecasts for the Welsh Government and is capable of forecasting passenger numbers for new stations located anywhere in GB.
Implementation of the model on DAFNI makes this powerful tool directly available to transport planning practitioners and other stakeholders for the first time. The data storage and transformation capabilities of DAFNI ensure that the model inputs are always available and up-to-date, freeing practitioners from onerous collection and processing tasks. The tool has the potential to transform the assessment of new station schemes, enabling the rapid review of options for individual stations or new lines. It can replace costly models developed on an ad hoc basis when a local need arises and can be a useful comparator tool to help assess the reliability of forecasts produced by locally developed models.
Young, Marcus
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Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Gowland, Tom
5c581efa-7d0b-4b37-9dd1-6585749316b9
Nagella, Srikanth
03b909fa-bc0a-4343-92e6-4261edbd2867
10 July 2019
Young, Marcus
b7679822-1e61-47d0-b7bf-3e33a12fa8fe
Blainey, Simon
ee6198e5-1f89-4f9b-be8e-52cc10e8b3bb
Gowland, Tom
5c581efa-7d0b-4b37-9dd1-6585749316b9
Nagella, Srikanth
03b909fa-bc0a-4343-92e6-4261edbd2867
Young, Marcus, Blainey, Simon, Gowland, Tom and Nagella, Srikanth
(2019)
An automated online tool to forecast demand for new railway stations and analyse potential abstraction effects.
The 17th Annual Transport Practitioners' Meeting, The Examination Schools, Oxford, United Kingdom.
10 - 11 Jul 2019.
Record type:
Conference or Workshop Item
(Paper)
Abstract
A national trip end model to forecast demand for new local railway stations in Great Britain has been developed and implemented as an automated hosted tool on the Data and Analytics Facility for National Infrastructure (DAFNI). This paper presentation describes the novel characteristics of the underlying model, explains how it has been realised on DAFNI, and incorporates a live demonstration of the tool’s web interface.
The underlying trip end model was calibrated on all existing local stations in mainland GB, and is unique in its scale, adoption of a high spatial resolution zoning system (trip generation is assessed for every postcode), and the incorporation of a station choice model. The latter allows probability-based station catchments to be defined, accounting for competition between stations and enabling the assessment of abstraction effects on existing stations. Testing of the model found that it produced more accurate demand forecasts than methods used during the scheme appraisal process for several recently opened stations and a new line. The model has already been used to produce demand forecasts for the Welsh Government and is capable of forecasting passenger numbers for new stations located anywhere in GB.
Implementation of the model on DAFNI makes this powerful tool directly available to transport planning practitioners and other stakeholders for the first time. The data storage and transformation capabilities of DAFNI ensure that the model inputs are always available and up-to-date, freeing practitioners from onerous collection and processing tasks. The tool has the potential to transform the assessment of new station schemes, enabling the rapid review of options for individual stations or new lines. It can replace costly models developed on an ad hoc basis when a local need arises and can be a useful comparator tool to help assess the reliability of forecasts produced by locally developed models.
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An automated online tool to forecast demand for new railway stations
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Published date: 10 July 2019
Venue - Dates:
The 17th Annual Transport Practitioners' Meeting, The Examination Schools, Oxford, United Kingdom, 2019-07-10 - 2019-07-11
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Local EPrints ID: 432493
URI: http://eprints.soton.ac.uk/id/eprint/432493
PURE UUID: 53e613c2-f320-4917-bc9f-2301910605a7
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Date deposited: 17 Jul 2019 16:30
Last modified: 16 Mar 2024 04:37
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Author:
Tom Gowland
Author:
Srikanth Nagella
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