Cantarella, GE and Watling, DP orcid.org/0000-0002-6193-9121 (2016) A General Stochastic Process for Day-to-Day Dynamic Traffic Assignment: Formulation, Asymptotic Behaviour, and Stability Analysis. Transportation Research Part B: Methodological, 92 (Part A). pp. 3-21. ISSN 0191-2615
Abstract
This paper presents a general modelling approach to day-to-day dynamic assignment to a congested network through discrete-time stochastic and deterministic process models including an explicit modelling of users’ habit as a part of route choice behaviour, through an exponential smoothing filter, and of their memory of network conditions on past days, through a moving average or an exponentially smoothing filter. An asymptotic analysis of the mean process is carried out to provide a better insight. Results of such analyses are also used for deriving conditions, about values of the system parameters, assuring that the mean process is dissipative and/or converges to some kind of attractor. Numerical small examples are also provided in order to illustrate the theoretical results obtained.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Published by Elsevier Ltd. This is an author produced version of a paper published in Transportation Research Part B: Methodological. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | day-to-day dynamics; stochastic process models; mean process; deterministic process models; stability analysis |
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: Spatial Modelling and Dynamics (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/I00212X/2 |
Depositing User: | Symplectic Publications |
Date Deposited: | 12 May 2016 10:36 |
Last Modified: | 18 Jan 2023 14:57 |
Published Version: | https://doi.org/10.1016/j.trb.2016.05.005 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.trb.2016.05.005 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:99558 |