A Dynamic Network Loading Model for Hub Station Pedestrian Flow Collection and Distribution

Weihao Zheng () and Ruifang Mou
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Weihao Zheng: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Ruifang Mou: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China

Mathematics, 2023, vol. 11, issue 17, 1-28

Abstract: A macro network loading model for multi-flow lines, time varying, and pedestrian congestion is proposed. The station hub is abstracted as a network of different types of nodes, and the flow of passengers at each node is calculated in real time for the purpose of simulating the hub’s collection and distribution process. For correct transmission of passenger flow on heterogeneous networks, three types of indexes are proposed to distinguish the nodes, and the corresponding fundamental diagrams are then matched. This paper divides the update process of the dynamic network loading model into multiple processes by flow lines, and improves the computational speed of the DNL model. The proposed model is applied to the simulation of passenger flow collection and distribution in an actual hub station with multi-flow lines. The analysis results illustrate that the model can accurately reflect the realistic congestion facilities and explain the formation process of high-density areas. A rolling passenger flow control model based on optimal control theory is proposed. The effectiveness of the control model is verified based on simulation data.

Keywords: macroscopic pedestrian flow model; passenger collection and distribution; dynamic network loading model; optimal control theory (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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