posted on 2017-02-14, 04:25authored byViet Quang Vo
Human crowd modelling
has gained importance for floor plan designs and crowd movement management. It
increases the need for more realistic modelling of human-like behaviours. The
state of the art in modelling studies often focuses on homogeneous crowds.
Grouping behaviour has been rarely addressed. Social studies show that crowds
are often inhomogeneous, which are containing different social groups. How
groups in crowds interact with each other has been rarely investigated.
Exploring the interactions of groups in such inhomogeneous crowds becomes
important to understand its impact on crowd movement. Therefore, this study
aims to model the dynamics of inhomogeneous crowds including group
interactions.
This study starts by building a model that captures the
grouping behaviour of individuals in an inhomogeneous crowd. The formation of
grouping and non-grouping behaviours was investigated by simulating the model
in a narrowing corridor, a turning corridor, a T-intersection corridor, and a
corridor with an obstacle. The results of the simulations of grouping and
non-grouping behaviours were analysed to explore which behaviour was effective
for crowd movement.
This study found that grouping behaviour helped to achieve
potential flow rates by preventing turbulence. In contrast, non-grouping
behaviour created turbulent flows of individuals and inefficient movement. This
study suggests that letting groups stay together is potentially effective for
crowd management when a large number of individuals are egressing the venue.
History
Campus location
Australia
Principal supervisor
Bernd Meyer
Additional supervisor 1
Aldeida Aleti
Year of Award
2017
Department, School or Centre
Information Technology (Monash University Caulfield)