Rail journey recovery following an incident
Rail journey recovery following an incident
Media coverage and personal experience tend to suggest that rail transport in Britain is unreliable. This negative image is to some extent a consequence of long-term under-investment in the railways, but the situation is exacerbated by rail’s inherent operational inflexibility relative to other modes. This characteristic means that rail transport is particularly vulnerable to disruptive incidents, which can cause rapid and widespread disruption and delay to train services. There are two broad, complementary responses to this situation: (i) investment in capacity and reliability, which is long-term and expensive; and (ii) the development and implementation of improved responses to disruptive events. A fundamental measure of rail’s performance is the delay incurred by trains, passengers and freight, and the minimisation of delay is one of the major goals of disruption management and of the regulation of trains when disruptions occur.
In order to prevent and measure train delay, accurate journey time information is required. In order to reduce, and, ideally minimise delay when disruptive events occur, it is useful to be able to simulate a range of possible responses. Such techniques also have wider applicability in railway operations planning. Following a review of the underlying issues, this thesis describes the development of two computer models to address these requirements. These models are also of use to Arup, the Industrial Sponsor of the research activity.
The need for improved methods of train regulation has been acknowledged within the British railway industry. Existing methods have some significant shortcomings, particularly with regard to the current system of train classification and the issue of regulating multiple trains. An alternative, improved classification system is proposed, together with the application of recognised scheduling techniques to multiple train regulation, and their potential benefits are demonstrated.
University of Southampton
Armstrong, John
ba42eda3-6147-4486-bab4-026d9dc68d83
2004
Armstrong, John
ba42eda3-6147-4486-bab4-026d9dc68d83
Armstrong, John
(2004)
Rail journey recovery following an incident.
University of Southampton, Doctoral Thesis.
Record type:
Thesis
(Doctoral)
Abstract
Media coverage and personal experience tend to suggest that rail transport in Britain is unreliable. This negative image is to some extent a consequence of long-term under-investment in the railways, but the situation is exacerbated by rail’s inherent operational inflexibility relative to other modes. This characteristic means that rail transport is particularly vulnerable to disruptive incidents, which can cause rapid and widespread disruption and delay to train services. There are two broad, complementary responses to this situation: (i) investment in capacity and reliability, which is long-term and expensive; and (ii) the development and implementation of improved responses to disruptive events. A fundamental measure of rail’s performance is the delay incurred by trains, passengers and freight, and the minimisation of delay is one of the major goals of disruption management and of the regulation of trains when disruptions occur.
In order to prevent and measure train delay, accurate journey time information is required. In order to reduce, and, ideally minimise delay when disruptive events occur, it is useful to be able to simulate a range of possible responses. Such techniques also have wider applicability in railway operations planning. Following a review of the underlying issues, this thesis describes the development of two computer models to address these requirements. These models are also of use to Arup, the Industrial Sponsor of the research activity.
The need for improved methods of train regulation has been acknowledged within the British railway industry. Existing methods have some significant shortcomings, particularly with regard to the current system of train classification and the issue of regulating multiple trains. An alternative, improved classification system is proposed, together with the application of recognised scheduling techniques to multiple train regulation, and their potential benefits are demonstrated.
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Published date: 2004
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Local EPrints ID: 465470
URI: http://eprints.soton.ac.uk/id/eprint/465470
PURE UUID: d2f593c0-5241-45fe-907f-ede2699a9de4
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Date deposited: 05 Jul 2022 01:14
Last modified: 16 Mar 2024 20:12
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Author:
John Armstrong
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