Leahy, C, Batley, R orcid.org/0000-0002-2487-850X and Chen, H (2016) Toward an Automated Methodology for the Valuation of Reliability. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 20 (4). pp. 334-344. ISSN 1547-2450
Abstract
There is a significant body of research related to the valuation of reliability in transportation. Such work has tended to rely on the Stated Preference (SP) methodology where respondents are asked to make trade-offs between the mean and standard deviation of travel time. The literature has suggested that a Revealed Preference (RP) methodology may provide an alternative means of estimating a value of reliability. In this paper we show how emerging data sources reveal travellers' preferences and, in combination with traditional choice modelling methods, can be used to estimate a value of reliability. We illustrate this RP methodology using smart card data from the multi-modal public transport network of London, UK. We are able to estimate a useable ‘Reliability Ratio’ for three of four public transport modes modelled, and account for an unexpected result based upon the data available.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2015, Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Intelligent Transportation Systems: Technology, Planning, and Operations on 18/09/15 available online: http://wwww.tandfonline.com/10.1080/15472450.2015.1091736 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Economics and Discrete Choice (Leeds) The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Oct 2015 09:00 |
Last Modified: | 27 Nov 2016 05:44 |
Published Version: | http://dx.doi.org/10.1080/15472450.2015.1091736 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/15472450.2015.1091736 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:91047 |