A force-based model for adaptively controlling the spatial configuration of pedestrian subgroups at non-extreme densities

The study of crowd dynamics has provided new insights into the understanding of human collective motion. However, most previous studies treated large-scale crowds as consisting of isolated individuals, but ignored the fact that pedestrian subgroups are prevalent in reality. With the increasing advancement of computer simulations, the critical role of subgroups in crowd modeling has been gradually recognized. Here, the authors develop a force-based model to reproduce the walking behaviors of pedestrian subgroups, in which the quantitative laws extracted from public datasets are incorporated for controlling their spatial configurations at different non-extreme densities. Numerical simulations indicate that the model achieves the simulation of pedestrian subgroups that coincides with empirical observations, and presents better simulation performance than existing subgroup models. The presence of pedestrian subgroups has also been confirmed to have certain effects on both fundamental diagrams and lane formation. Overall, this paper contributes a valuable framework to the modeling of pedestrian subgroups for guiding relevant implementations in potential application areas.

• Record URL:
  • https://doi.org/10.1016/j.trc.2023.104154
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0968090X23001432
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Wu, Wenhan
  • 0000-0003-4487-9283
  • Yi, Wenfeng
  • Wang, Xiaolu
  • Zheng, Xiaoping
  • 0000-0002-2935-9514
• Publication Date: 2023-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 104154
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 152
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Behavior; Crowds; Pedestrians; Simulation; Walking
• Subject Areas: Pedestrians and Bicyclists; Planning and Forecasting;

Filing Info

• Accession Number: 01889884
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 11 2023 12:05PM