Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management

Yasufuku, Kensuke; Takahashi, Akira

Journal of Disaster Research, 2024, 19(2), 248-255

Number of Access:688（2026-02-18 05:50 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/101000

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Title
Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management
Creator
NRID
1000020452386 1000020452386
ORCID
0000-0003-0525-7326 0000-0003-0525-7326
researchmap permalink
read0203282 read0203282
Scopus Author ID
37113492300 37113492300
CreatorName
Yasufuku, Kensuke
NRID
1000040885464 1000040885464
ORCID
0000-0002-8376-4027 0000-0002-8376-4027
researchmap permalink
takahashi_akira takahashi_akira
Scopus Author ID
55728345200 55728345200
CreatorName
Takahashi, Akira
Subject
crowd flow prediction
crowd managemenagent-based simulation
visualization
Description
Yasufuku K., Takahashi A.. Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management. Journal of Disaster Research 19, 248 (2024); https://doi.org/10.20965/jdr.2024.p0248.
Abstract
Crowd management at large-scale events and specific facilities is a critical issue from the perspectives of safety and service quality improvement. Traditional methods for crowd management often rely on empirical knowledge, which has limitations in quickly grasping the on-site situation and making decisions on the spot. In this study, we developed a real-time crowd flow prediction and visualization platform incorporating an agent-based crowd simulation and an advanced crowd management system called crowd management platform as a service. In a case study focused on the area around the Tokyo Dome, we demonstrated that capturing pedestrian flow allows for accurate predictions of congestion at the nearest train station up to 10 min in advance. Moreover, the time required to predict the situation 20 min ahead for 3,000 agents was 1 min and 35 s, confirming the feasibility of real-time processing. To enhance the accuracy and reliability of the simulation results, a sensitivity analysis considering errors in pedestrian flow measurement revealed that simple linear models cannot capture the complexity of crowd dynamics adequately. Notably, the agent-based simulation replicated stop-and-go wave patterns observed in actual measurements under specific crowd conditions, confirming the advantage of using agent-based simulations. Finally, we proposed a method that enables facility managers and security personnel to conduct a more comprehensive evaluation. This method integrates their existing experience with the aggregated display of multiple simulation results, which includes consideration of errors in pedestrian flow measurement through a visualization platform.
Publisher
Fuji Technology Press
Source Title
Journal of Disaster Research
Volume (Issue)
19(2)
Page
248-255
Date of Issued
2024-04-01
Language
English
Handle URL
https://hdl.handle.net/11094/101000
PISSN
18812473
eISSN
18838030
Relation.isIdenticalTo
DOI (Publisher Version)
https://doi.org/10.20965/jdr.2024.p0248
Access Rights
open access
CopyRight
This article is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
oaire:version
Version of Record
Category
学術雑誌論文 Journal Article