Ye, H, Xiao, F and Yang, H (2018) Exploration of day-to-day route choice models by a virtual experiment. Transportation Research Part C: Emerging Technologies, 94. pp. 220-235. ISSN 0968-090X
Abstract
This paper examines existing day-to-day models based on a virtual day-to-day route choice experiment using the latest mobile Internet technologies. With the realized day-to-day path flows and path travel times in the experiment, we calibrate several well-designed path-based day-to-day models that take the Wardrop’s user equilibrium as (part of) their stationary states. The nonlinear effects of path flows and path time differences on path switching are then investigated. Participants’ path preferences, time-varying sensitivity, and learning behavior in the day-to-day process are also examined. The prediction power of various models with various settings (nonlinear effects, time-varying sensitivity, and learning) is compared. The assumption of “rational behavior adjustment process” in Yang and Zhang (2009) is further verified. Finally, evolutions of different Lyapunov functions used in the literature are plotted, and no obvious diversity is observed.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2017, Elsevier Ltd. All rights reserved. This is an author produced version of a paper published in Transportation Research Part C: Emerging Technologies. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Day-to-day flow dynamics; Virtual route choice experiment; Regression analysis; Model calibration; Model comparison |
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) |
Depositing User: | Symplectic Publications |
Date Deposited: | 15 Sep 2017 15:26 |
Last Modified: | 14 Sep 2018 11:24 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.trc.2017.08.020 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:121278 |