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Title: A discrete day-to-day link flow dynamic model considering travelers' heterogeneous inertia patterns
Authors: Zhou, BJ
Xu, M 
Meng, Q
Issue Date: 2020
Source: Transportmetrica. A, Transport science, 2020, v. 16, no. 3, p. 1400-1428
Abstract: This study investigates the impact of heterogeneous psychological inertia of travelers on link flow evolution process on a day-to-day basis. The psychological inertia of a traveler is defined as his/her reluctance to reconsider his/her route choice, and is characterized by a sequence of binary parameters along time. Travelers are grouped into different classes by their inertia patterns. Based on these classes, a variational inequality formulation for the multi-class user equilibrium problem is presented. We develop a generic day-to-day link flow dynamic model by considering heterogeneous inertia patterns of the travelers. The convergence properties of the model are rigorously demonstrated. The developed model is formulated in a general form under mild assumptions. We further consider a special case of the generic model. We examine properties of this special case model, and investigate its relationship with existing models in the literature. Numerical experiments are conducted to demonstrate our theoretical results.
Keywords: Inertia pattern
Class-based formulation
Heterogeneous psychological inertia
Link flow adjustment model
Publisher: Taylor & Francis
Journal: Transportmetrica. A, Transport science 
ISSN: 2324-9935
EISSN: 2324-9943
DOI: 10.1080/23249935.2020.1749961
Rights: © 2020 Hong Kong Society for Transportation Studies Limited
This is an Accepted Manuscript of an article published by Taylor & Francis in Transportmetrica A: Transport Science on 16 Apr 2020 (Published online), available online:
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