| Issue |
EPJ Web Conf.
Volume 334, 2025
Traffic and Granular Flow 2024 (TGF’24)
|
|
|---|---|---|
| Article Number | 04017 | |
| Number of page(s) | 9 | |
| Section | Pedestrian Dynamics | |
| DOI | https://doi.org/10.1051/epjconf/202533404017 | |
| Published online | 12 September 2025 | |
https://doi.org/10.1051/epjconf/202533404017
Speed and Velocity Variance: An approach to analyzing crowd congestion dynamics
1 School of Engineering, The University of Tokyo, Tokyo, Japan
2 Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, China
* E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 12 September 2025
Abstract
Crowd dynamics, particularly in high-density scenarios, pose significant challenges for congestion analysis and risk mitigation. This study introduces novel metrics, speed and velocity variances, to evaluate crowd congestion. By approximating individuals to special particles, speed/velocity variance quantifies movement irregularity, offering a unique perspective on congestion levels. The proposed concept was applied on experimental data from a T-shaped merging corridor. Experimental analyses with varying densities and turning angles demonstrate speed/velocity variance effectiveness in capturing localized disruptions and pre-collision risks. The findings highlight speed/velocity variance's sensitivity to both individual and group dynamics, providing a higher resolution compared to traditional metrics such as density and the recently proposed congestion number. Moreover, speed/velocity variance's dependency on turning angles and crowd size underscores its potential for real-time monitoring and enhanced predictive capabilities in complex scenarios.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

