Preston, J.M. and Nash, C.A. (1986) Some Guidelines for Evaluating New Local Rail Stations. Working Paper. Institute of Transport Studies, University of Leeds , Leeds, UK.Full text available as:
Available under License : See the attached licence file.
This paper, based on vark undertaken as part of a Ph.D. studentship on new local rail staticms in West Yorkshire, seeks to offer guidelines for identifying and appraising new local rail station sites, and recommendations for further work on the subject. It outlines three methods of forecasting demand at such stations - a simple method based on mean trip rates at certain distance bands for similar existing new stations, an aggregate regression model, and a combination of a disaggregate mode split model for the journey to work with an aggregate non-work journey model. Whilst the latter models do provide greater accuracy, it is suggested that a simple trip-rate model may be adequate for one-off low-cost stations, although packages of stations and train service alterations need more thorough investigation. On this basis, it is suggested that for new stations with the characteristics of those in West Yorkshire (i.e. suburban stations in residential areas a few miles from major employment centres), sites which are free of significant engineering problems, with good road access, close to an existing bridge or crossing and with a population of at least 2,000 within 800 metres of the site, should be sought. On single track rural branch lines, new stations may be justified at much lower population levels.
|Item Type:||Monograph (Working Paper)|
|Copyright, Publisher and Additional Information:||Copyright of the Institute of Transport Studies, University Of Leeds.|
|Academic Units:||The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)|
|Depositing User:||Adrian May|
|Date Deposited:||12 Apr 2007|
|Last Modified:||08 Feb 2013 17:04|
|Publisher:||Institute of Transport Studies, University of Leeds|
|Identification Number:||Working Paper 228|
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