Simulating Crowds in Real Time with Agent-Based Modelling and a Particle Filter

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dc.contributor.author Malleson, Nick
dc.contributor.author Minors, Kevin
dc.contributor.author Kieu, Le-Minh
dc.contributor.author Ward, Jonathan A
dc.contributor.author West, Andrew
dc.contributor.author Heppenstall, Alison
dc.date.accessioned 2021-12-12T23:13:24Z
dc.date.available 2021-12-12T23:13:24Z
dc.date.issued 2020-1-1
dc.identifier.citation Journal of Artificial Societies and Social Simulation 23(3) 01 Jan 2020
dc.identifier.issn 1460-7425
dc.identifier.uri https://hdl.handle.net/2292/57739
dc.description.abstract Agent-based modelling is a valuable approach for modelling systems whose behaviour is driven by the interactions between distinct entities, such as crowds of people. However, it faces a fundamental difficulty: there are no established mechanisms for dynamically incorporating real-time data into models. This limits simulations that are inherently dynamic, such as those of pedestrian movements, to scenario testing on historic patterns rather than real-time simulation of the present. This paper demonstrates how a particle filter could be used to incorporate data into an agent-based model of pedestrian movements at run time. The experiments show that although it is possible to use a particle filter to perform online (real time) model optimisation, the number of individual particles required (and hence the computational complexity) increases exponentially with the number of agents. Furthermore, the paper assumes a one-to-one mapping between observations and individual agents, which would not be the case in reality. Therefore this paper lays some of the fundamental groundwork and highlights the key challenges that need to be addressed for the real-time simulation of crowd movements to become a reality. Such success could have implications for the management of complex environments both nationally and internationally such as transportation hubs, hospitals, shopping centres, etc.
dc.language en
dc.publisher Journal of Artificial Societies and Social Simulation
dc.relation.ispartofseries Journal of Artificial Societies and Social Simulation
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject 0406 Physical Geography and Environmental Geoscience
dc.subject 0801 Artificial Intelligence and Image Processing
dc.subject 1608 Sociology
dc.title Simulating Crowds in Real Time with Agent-Based Modelling and a Particle Filter
dc.type Journal Article
dc.identifier.doi 10.18564/jasss.4266
pubs.issue 3
pubs.begin-page 1
pubs.volume 23
dc.date.updated 2021-11-18T20:50:09Z
dc.rights.holder Copyright: JASS en
pubs.end-page 20
pubs.publication-status Published online
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Journal Article
pubs.elements-id 816732
dc.identifier.eissn 1460-7425
pubs.online-publication-date 2020


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