Forecasting Crowd Movements in Real-Time

Forecasting Crowd Movements in Real-Time: A database-driven approach for real-time prediction of crowd movement during mass events

Godoy, Paula (TU Delft Civil Engineering and Geosciences)

Sparnaaij, M. (mentor)
Duives, D.C. (graduation committee)
van Lint, J.W.C. (graduation committee)
Yuan, Y. (graduation committee)
Valkhoff, N. (mentor)

Delft University of Technology

Civil Engineering | Transport and Planning

2020-12-15

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.

crowd
real-time prediction
database-driven
mass event

http://resolver.tudelft.nl/uuid:606424e1-9d77-48c6-9436-4d13c7adfbba

Student theses

master thesis

© 2020 Paula Godoy