Multi-column Partitioning for Agent-based CA Model

Autores
Tissera, Pablo Cristian; Printista, Alicia Marcela; Errecalde, Marcelo Luis
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Computer simulations using Cellular Automata (CA) have been applied with considerable success in different scientific areas, such as chemistry, biochemistry, economy, physics, etc. In this work we use CA in order to specify and implement a simulation model that allows to investigate behavioural dynamics for pedestrians in an emergency evacuation. Two important aspects must be considered when simulating the movement of people: a) estimation of distances from the cells to an exit and b) handling of collisions between individuals. For the first problem, the Dijkstra algorithm was used. In relation to the collisions, we proposed two approaches to solve the movement of people: centralised on a empty cell and distributed in the neighbouring cells. This latter approach leads to the formulation of Agent-based CA Model for pedestrians motion. Finally, in order to accelerate the simulation and take advantage of modern computer architectures, the paper also presents a parallel implementation which is an adaptation of the traditional Ghost Cell Pattern technique. This implementation will be essential when the model complexity increases due to the incorporation of new features. We apply our approaches to several environment configurations achieving important reduction of simulation time.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Evacuation Simulation
Parallel Cellular Automata
Pedestrian Motion
Agents
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/126129

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spelling Multi-column Partitioning for Agent-based CA ModelTissera, Pablo CristianPrintista, Alicia MarcelaErrecalde, Marcelo LuisCiencias InformáticasEvacuation SimulationParallel Cellular AutomataPedestrian MotionAgentsComputer simulations using Cellular Automata (CA) have been applied with considerable success in different scientific areas, such as chemistry, biochemistry, economy, physics, etc. In this work we use CA in order to specify and implement a simulation model that allows to investigate behavioural dynamics for pedestrians in an emergency evacuation. Two important aspects must be considered when simulating the movement of people: a) estimation of distances from the cells to an exit and b) handling of collisions between individuals. For the first problem, the Dijkstra algorithm was used. In relation to the collisions, we proposed two approaches to solve the movement of people: centralised on a empty cell and distributed in the neighbouring cells. This latter approach leads to the formulation of Agent-based CA Model for pedestrians motion. Finally, in order to accelerate the simulation and take advantage of modern computer architectures, the paper also presents a parallel implementation which is an adaptation of the traditional Ghost Cell Pattern technique. This implementation will be essential when the model complexity increases due to the incorporation of new features. We apply our approaches to several environment configurations achieving important reduction of simulation time.Sociedad Argentina de Informática e Investigación Operativa2011-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf89-103http://sedici.unlp.edu.ar/handle/10915/126129enginfo:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/993.pdfinfo:eu-repo/semantics/altIdentifier/issn/1851-9326info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:22:16Zoai:sedici.unlp.edu.ar:10915/126129Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:22:17.056SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Multi-column Partitioning for Agent-based CA Model
title Multi-column Partitioning for Agent-based CA Model
spellingShingle Multi-column Partitioning for Agent-based CA Model
Tissera, Pablo Cristian
Ciencias Informáticas
Evacuation Simulation
Parallel Cellular Automata
Pedestrian Motion
Agents
title_short Multi-column Partitioning for Agent-based CA Model
title_full Multi-column Partitioning for Agent-based CA Model
title_fullStr Multi-column Partitioning for Agent-based CA Model
title_full_unstemmed Multi-column Partitioning for Agent-based CA Model
title_sort Multi-column Partitioning for Agent-based CA Model
dc.creator.none.fl_str_mv Tissera, Pablo Cristian
Printista, Alicia Marcela
Errecalde, Marcelo Luis
author Tissera, Pablo Cristian
author_facet Tissera, Pablo Cristian
Printista, Alicia Marcela
Errecalde, Marcelo Luis
author_role author
author2 Printista, Alicia Marcela
Errecalde, Marcelo Luis
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Evacuation Simulation
Parallel Cellular Automata
Pedestrian Motion
Agents
topic Ciencias Informáticas
Evacuation Simulation
Parallel Cellular Automata
Pedestrian Motion
Agents
dc.description.none.fl_txt_mv Computer simulations using Cellular Automata (CA) have been applied with considerable success in different scientific areas, such as chemistry, biochemistry, economy, physics, etc. In this work we use CA in order to specify and implement a simulation model that allows to investigate behavioural dynamics for pedestrians in an emergency evacuation. Two important aspects must be considered when simulating the movement of people: a) estimation of distances from the cells to an exit and b) handling of collisions between individuals. For the first problem, the Dijkstra algorithm was used. In relation to the collisions, we proposed two approaches to solve the movement of people: centralised on a empty cell and distributed in the neighbouring cells. This latter approach leads to the formulation of Agent-based CA Model for pedestrians motion. Finally, in order to accelerate the simulation and take advantage of modern computer architectures, the paper also presents a parallel implementation which is an adaptation of the traditional Ghost Cell Pattern technique. This implementation will be essential when the model complexity increases due to the incorporation of new features. We apply our approaches to several environment configurations achieving important reduction of simulation time.
Sociedad Argentina de Informática e Investigación Operativa
description Computer simulations using Cellular Automata (CA) have been applied with considerable success in different scientific areas, such as chemistry, biochemistry, economy, physics, etc. In this work we use CA in order to specify and implement a simulation model that allows to investigate behavioural dynamics for pedestrians in an emergency evacuation. Two important aspects must be considered when simulating the movement of people: a) estimation of distances from the cells to an exit and b) handling of collisions between individuals. For the first problem, the Dijkstra algorithm was used. In relation to the collisions, we proposed two approaches to solve the movement of people: centralised on a empty cell and distributed in the neighbouring cells. This latter approach leads to the formulation of Agent-based CA Model for pedestrians motion. Finally, in order to accelerate the simulation and take advantage of modern computer architectures, the paper also presents a parallel implementation which is an adaptation of the traditional Ghost Cell Pattern technique. This implementation will be essential when the model complexity increases due to the incorporation of new features. We apply our approaches to several environment configurations achieving important reduction of simulation time.
publishDate 2011
dc.date.none.fl_str_mv 2011-08
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
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