Forecasting Crowd Movements in Real-Time

A database-driven approach for real-time prediction of crowd movement during mass events

Master thesis (2020)

Authors

P. Godoy Civil Engineering & Geosciences

Contributors

M. Sparnaaij Transport and Planning - CEG (supervisor 1)
D.C. Duives Transport and Planning - CEG (supervisor 2)
J.W.C. van Lint Transport and Planning - CEG (supervisor 2)
Y. Yuan Transport and Planning - CEG (supervisor 2)
N. Valkhoff INCONTROL Simulation Solutions (supervisor 1)
Faculty
Civil Engineering & Geosciences
Copyright: © 2020 Paula Godoy
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Published Date

15-12-2020

Language

English

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Faculty

Civil Engineering & Geosciences

Abstract

Predicting crowd movements in real-time during mass events has been shown to be a complex yet valuable task in order to reduce the risk of overcrowding. The aim of this research is to propose and validate a crowd movement forecasting method for which simulation is performed offline (i.e. prior to the event) but the forecast is done online, in real-time. A number of scenarios is formulated and simulated creating what is called a database of scenarios. In real-time, based on information from the event's crowd monitoring systems, a scenario from this database is then selected which corresponds to the prediction. The research is focused on addressing the concepts related to the two pillars of the method: the formulation of the scenarios to be included in the database, and the operationalization of the system to select a scenario in real-time.