Amos, Martyn, Gainer, Paul, Gwynne, Steve ORCID: https://orcid.org/0000-0002-2758-3897, Templeton, Anne and Kimball, Amanda (2024) A dynamic state-based model of crowds. Safety Science. ISSN 0925-7535 (Print), 1879-1042 (Online) (doi:10.1016/j.ssci.2024.106522)

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Abstract

We consider the problem of categorising, describing and generating the dynamic properties and behaviours of crowds over time. Previous work has tended to focus on a relatively static “typology”-based approach, which does not account for the fact that crowds can change, often quite rapidly. Moreover, the labels attached to crowd behaviours are often subjective and/or value-laden. Here, we present an alternative approach which uses relatively “agnostic” labels. This means that we do not prescribe the behaviour of an individual, but provide a context within which an individual might behave. This naturally describes the time-series evolution of a crowd, and allows for the dynamic handling of an arbitrary number of “sub-crowds”. Apart from its descriptive power (capturing, in a standardised manner, descriptions of known events), our model may also be used generatively to produce plausible patterns of crowd dynamics and as a component of machine learning-based approaches to investigating behaviour and interventions.

Item Type:	Article
Uncontrolled Keywords:	crowd, typology, model, statechart, event analysis, simulation
Subjects:	H Social Sciences > H Social Sciences (General) Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Last Modified:	18 Nov 2025 16:38
URI:	https://gala.gre.ac.uk/id/eprint/51617

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