Train Operation Diagram–Based Equilibrium Model for an Urban Rail Transit Network with Transfer Constraints
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 11
Abstract
For urban rail transit (URT) operation and management, it is important to accurately estimate the spatial and temporal passenger flow distribution spreading all over the network. Unfortunately, a literature review shows that the existing simulation-based methods and dynamic assignment methods are not able to satisfactorily achieve the goal. Therefore, this paper proposes a train operation diagram–based equilibrium model to estimate the spatial and temporal passenger flow distribution in a URT network. First, a space-time URT network is constructed based on the train operation diagram, and then an equilibrium passenger flow assignment model is proposed for a URT system. Factors including travel time, transfer time, in-train congestion, and station congestion are considered. An improved shortest-path algorithm for the space-time URT network is presented, in which the transfer constraints are fully considered. Finally, the proposed model and algorithm are verified and analyzed by using a numerical example and are also demonstrated in the Beijing URT network. The proposed model, which is based on the train operation diagram and with the consideration of transfer constraints, is beneficial to estimating passenger flow within a URT network and to managing URT.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The research is funded by the National Key Research and Development Program of China (No. 2018YFB1601300) and National Natural Science Foundation of China (Nos. 71571013, 71871010, 71210001, and 71621001).
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 11 • November 2020
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© 2020 American Society of Civil Engineers.
History
Received: Oct 10, 2019
Accepted: Jun 4, 2020
Published online: Aug 20, 2020
Published in print: Nov 1, 2020
Discussion open until: Jan 20, 2021
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