Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96005
PIRA download icon_1.1View/Download Full Text
Title: A dynamic network loading model for anisotropic and congested pedestrian flows
Authors: Hänseler, FS 
Lam, WHK 
Bierlaire, M
Lederrey, G
Nikolić, M
Issue Date: Jan-2017
Source: Transportation research. Part B, Methodological, Jan. 2017, v. 95, p. 149-168
Abstract: A macroscopic loading model for multi-directional, time-varying and congested pedestrian flows is proposed. Walkable space is represented by a network of streams that are each associated with an area in which they interact. To describe this interaction, a stream-based pedestrian fundamental diagram is used that relates density and walking speed in multi-directional flow. The proposed model is applied to two different case studies. The explicit modeling of anisotropy in walking speed is shown to significantly improve the ability of the model to reproduce empirically observed walking time distributions. Moreover, the obtained model parametrization is in excellent agreement with the literature.
Keywords: Anisotropy
Calibration
Macroscopic model
Network loading
Pedestrian flow
Pedestrian fundamental diagram
Publisher: Pergamon Press
Journal: Transportation research. Part B, Methodological 
ISSN: 0191-2615
EISSN: 1879-2367
DOI: 10.1016/j.trb.2016.10.017
Rights: © 2016 Elsevier Ltd. All rights reserved.
© 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
The following publication Hänseler, F. S., Lam, W. H. K., Bierlaire, M., Lederrey, G., & Nikolić, M. (2017). A dynamic network loading model for anisotropic and congested pedestrian flows. Transportation Research Part B: Methodological, 95, 149-168 is available at https://doi.org/10.1016/j.trb.2016.10.017.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Lam_Dynamic_Network_Loading.pdfPre-Published version1.12 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

46
Last Week
0
Last month
Citations as of May 19, 2024

Downloads

29
Citations as of May 19, 2024

SCOPUSTM   
Citations

41
Citations as of May 17, 2024

WEB OF SCIENCETM
Citations

39
Citations as of May 16, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.