Analysis of crowd behavior through pattern virtualization

The study of the concentration of individuals in public places such as squares, shopping malls, parks, gardens, etc., is an open study field in the different disciplines of science, that leads to the need of having systems that allow to forecast and to predict eventualities in uncontrolled situation...

Full description

Autores:
amelec, viloria
Pineda Lezama, Omar Bonerge
Vargas, Jesus
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7696
Acceso en línea:
https://hdl.handle.net/11323/7696
https://doi.org/10.1016/j.procs.2020.07.017
https://repositorio.cuc.edu.co/
Palabra clave:
Heterogeneous virtual crowds
Human behavior
Grouping patterns
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_35376753db59739a404943b243eaaf49
oai_identifier_str oai:repositorio.cuc.edu.co:11323/7696
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Analysis of crowd behavior through pattern virtualization
title Analysis of crowd behavior through pattern virtualization
spellingShingle Analysis of crowd behavior through pattern virtualization
Heterogeneous virtual crowds
Human behavior
Grouping patterns
title_short Analysis of crowd behavior through pattern virtualization
title_full Analysis of crowd behavior through pattern virtualization
title_fullStr Analysis of crowd behavior through pattern virtualization
title_full_unstemmed Analysis of crowd behavior through pattern virtualization
title_sort Analysis of crowd behavior through pattern virtualization
dc.creator.fl_str_mv amelec, viloria
Pineda Lezama, Omar Bonerge
Vargas, Jesus
dc.contributor.author.spa.fl_str_mv amelec, viloria
Pineda Lezama, Omar Bonerge
Vargas, Jesus
dc.subject.spa.fl_str_mv Heterogeneous virtual crowds
Human behavior
Grouping patterns
topic Heterogeneous virtual crowds
Human behavior
Grouping patterns
description The study of the concentration of individuals in public places such as squares, shopping malls, parks, gardens, etc., is an open study field in the different disciplines of science, that leads to the need of having systems that allow to forecast and to predict eventualities in uncontrolled situations, as it is the case of an earthquake. From that assumption, artificial intelligence, as a branch of computational sciences, studies the human behavior in a virtual way in order to obtain simulations based on social, psychological, neuro-scientific areas, among others, with the purpose of linking these theories to the area of artificial intelligence. This paper presents a way to generate virtual multitudes with heterogeneous behaviors, in such a way that the individuals that form the multitude present different behaviors.
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2021-01-15T14:16:13Z
dc.date.available.none.fl_str_mv 2021-01-15T14:16:13Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
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identifier_str_mv 1877-0509
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/7696
https://doi.org/10.1016/j.procs.2020.07.017
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv [1] Ma, Y. P., & Zhang, H. (2020). Simulation study on cooperation behaviors and crowd dynamics in pedestrian evacuation. Chinese Physics B.
[2] Liu, A. (2020). DYNAMIC VISUALIZATIONS: Developing a Framework for Crowd-Based Simulations (Master's thesis, University of Waterloo).
[3] Xu, M., Xie, X., Lv, P., Niu, J., Wang, H., Li, C., ... & Zhou, B. (2019). Crowd behavior simulation with emotional contagion in unexpected multihazard situations. IEEE Transactions on Systems, Man, and Cybernetics: Systems.
[4] Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. J. (2008). Crowd simulation for emergency response using BDI agents based on immersive virtual reality. Simulation Modelling Practice and Theory, 16(9), 1415-1429.
[5] Dickinson, P., Gerling, K., Hicks, K., Murray, J., Shearer, J., & Greenwood, J. (2019). Virtual reality crowd simulation: effects of agent density on user experience and behaviour. Virtual Reality, 23(1), 19-32.
[6] Miyagawa, D., & Ichinose, G. (2020). Cellular automaton model with turning behavior in crowd evacuation. Physica A: Statistical Mechanics and its Applications, 124376.
[7] Guy, S.J., Chhugani, J., Curtis, S., Dubey, P., Lin, M., Manocha, D.: Pledestrians: a least-effort approach to crowd simulation. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics symposium on computer animation. pp. 119–128. Eu- rographics Association (2010)
[8] Hadap, S., Eberle, D., Volino, P., Lin, M.C., Redon, S., Ericson, C.: Collision detection and proximity queries. In: ACM SIGGRAPH 2004 Course Notes. p. 15. ACM (2004)
[9] Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. J. (2006, December). Crowd simulation for emergency response using BDI agent based on virtual reality. In Proceedings of the 2006 winter simulation conference (pp. 545-553). IEEE.
[10] Kapadia, M., Singh, S., Reinman, G., Faloutsos, P.: A behavior-authoring frame- work for multiactor simulations. Computer Graphics and Applications, IEEE 31(6), 45–55 (2011)
[11] Ulicny, B., & Thalmann, D. (2001). Crowd simulation for interactive virtual environments and VR training systems. In Computer animation and simulation 2001 (pp. 163-170). Springer, Vienna.
[12] Xue, J., Yin, H., Lv, P., Xu, M., & Li, Y. (2019). Crowd queuing simulation with an improved emotional contagion model. Science China Information Sciences, 62(4), 44101.
[13] Pelechano, N., Allbeck, J.M., Badler, N.I.: Controlling individual agents in high-density crowd simulation. In: Proceedings of the 2007 ACM SIG- GRAPH/Eurographics symposium on Computer animation. pp. 99–108. Euro- graphics Association (2007)
[14] Zou, Q., & Chen, S. (2020). Simulation of Crowd Evacuation under Toxic Gas Incident Considering Emotion Contagion and Information Transmission. Journal of Computing in Civil Engineering, 34(3), 04020007.
[15] Samson, M., Crowe, A., De Vreede, P., Dessens, J., Duursma, S., Verhaar, H.: Differences in gait parameters at a preferred walking speed in healthy subjects due to age, height and body weight. Aging Clinical and Experimental Research 13(1), 16–21 (2001)
[16] Bera, A., Kim, S., & Manocha, D. (2016, March). Interactive and adaptive data-driven crowd simulation: User study. In 2016 IEEE Virtual Reality (VR) (pp. 325-325). IEEE.
[17] Vásquez, C., Ramírez-Pisco, R., Viloria, A., Martínez Sierra, D., Ruiz-Barrios, E., Hernández-P, H., … De la Hoz Hernández, J. (2020). Conglomerates of Bus Rapid Transit in Latin American Countries. In Advances in Intelligent Systems and Computing (Vol. 1039, pp. 220– 228). Springer. https://doi.org/10.1007/978-3-030-30465-2_25
[18] Viloria, A., & Pineda Lezama, O. B. (2019). An intelligent approach for the design and development of a personalized system of knowledge representation. In Procedia Computer Science (Vol. 151, pp. 1225–1230). Elsevier B.V. https://doi.org/10.1016/j.procs.2019.04.176
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dc.publisher.spa.fl_str_mv Corporación Universidad de la Costa
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spelling amelec, viloriaPineda Lezama, Omar BonergeVargas, Jesus2021-01-15T14:16:13Z2021-01-15T14:16:13Z20201877-0509https://hdl.handle.net/11323/7696https://doi.org/10.1016/j.procs.2020.07.017Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/The study of the concentration of individuals in public places such as squares, shopping malls, parks, gardens, etc., is an open study field in the different disciplines of science, that leads to the need of having systems that allow to forecast and to predict eventualities in uncontrolled situations, as it is the case of an earthquake. From that assumption, artificial intelligence, as a branch of computational sciences, studies the human behavior in a virtual way in order to obtain simulations based on social, psychological, neuro-scientific areas, among others, with the purpose of linking these theories to the area of artificial intelligence. This paper presents a way to generate virtual multitudes with heterogeneous behaviors, in such a way that the individuals that form the multitude present different behaviors.amelec, viloria-will be generated-orcid-0000-0003-2673-6350-600Pineda Lezama, Omar BonergeVargas, Jesusapplication/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Procedia Computer Sciencehttps://www.sciencedirect.com/science/article/pii/S1877050920316963Heterogeneous virtual crowdsHuman behaviorGrouping patternsAnalysis of crowd behavior through pattern virtualizationArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion[1] Ma, Y. P., & Zhang, H. (2020). Simulation study on cooperation behaviors and crowd dynamics in pedestrian evacuation. Chinese Physics B.[2] Liu, A. (2020). DYNAMIC VISUALIZATIONS: Developing a Framework for Crowd-Based Simulations (Master's thesis, University of Waterloo).[3] Xu, M., Xie, X., Lv, P., Niu, J., Wang, H., Li, C., ... & Zhou, B. (2019). Crowd behavior simulation with emotional contagion in unexpected multihazard situations. IEEE Transactions on Systems, Man, and Cybernetics: Systems.[4] Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. J. (2008). Crowd simulation for emergency response using BDI agents based on immersive virtual reality. Simulation Modelling Practice and Theory, 16(9), 1415-1429.[5] Dickinson, P., Gerling, K., Hicks, K., Murray, J., Shearer, J., & Greenwood, J. (2019). Virtual reality crowd simulation: effects of agent density on user experience and behaviour. Virtual Reality, 23(1), 19-32.[6] Miyagawa, D., & Ichinose, G. (2020). Cellular automaton model with turning behavior in crowd evacuation. Physica A: Statistical Mechanics and its Applications, 124376.[7] Guy, S.J., Chhugani, J., Curtis, S., Dubey, P., Lin, M., Manocha, D.: Pledestrians: a least-effort approach to crowd simulation. In: Proceedings of the 2010 ACM SIGGRAPH/Eurographics symposium on computer animation. pp. 119–128. Eu- rographics Association (2010)[8] Hadap, S., Eberle, D., Volino, P., Lin, M.C., Redon, S., Ericson, C.: Collision detection and proximity queries. In: ACM SIGGRAPH 2004 Course Notes. p. 15. ACM (2004)[9] Shendarkar, A., Vasudevan, K., Lee, S., & Son, Y. J. (2006, December). Crowd simulation for emergency response using BDI agent based on virtual reality. In Proceedings of the 2006 winter simulation conference (pp. 545-553). IEEE.[10] Kapadia, M., Singh, S., Reinman, G., Faloutsos, P.: A behavior-authoring frame- work for multiactor simulations. Computer Graphics and Applications, IEEE 31(6), 45–55 (2011)[11] Ulicny, B., & Thalmann, D. (2001). Crowd simulation for interactive virtual environments and VR training systems. In Computer animation and simulation 2001 (pp. 163-170). Springer, Vienna.[12] Xue, J., Yin, H., Lv, P., Xu, M., & Li, Y. (2019). Crowd queuing simulation with an improved emotional contagion model. Science China Information Sciences, 62(4), 44101.[13] Pelechano, N., Allbeck, J.M., Badler, N.I.: Controlling individual agents in high-density crowd simulation. In: Proceedings of the 2007 ACM SIG- GRAPH/Eurographics symposium on Computer animation. pp. 99–108. Euro- graphics Association (2007)[14] Zou, Q., & Chen, S. (2020). Simulation of Crowd Evacuation under Toxic Gas Incident Considering Emotion Contagion and Information Transmission. Journal of Computing in Civil Engineering, 34(3), 04020007.[15] Samson, M., Crowe, A., De Vreede, P., Dessens, J., Duursma, S., Verhaar, H.: Differences in gait parameters at a preferred walking speed in healthy subjects due to age, height and body weight. Aging Clinical and Experimental Research 13(1), 16–21 (2001)[16] Bera, A., Kim, S., & Manocha, D. (2016, March). Interactive and adaptive data-driven crowd simulation: User study. In 2016 IEEE Virtual Reality (VR) (pp. 325-325). IEEE.[17] Vásquez, C., Ramírez-Pisco, R., Viloria, A., Martínez Sierra, D., Ruiz-Barrios, E., Hernández-P, H., … De la Hoz Hernández, J. (2020). Conglomerates of Bus Rapid Transit in Latin American Countries. In Advances in Intelligent Systems and Computing (Vol. 1039, pp. 220– 228). Springer. https://doi.org/10.1007/978-3-030-30465-2_25[18] Viloria, A., & Pineda Lezama, O. B. (2019). An intelligent approach for the design and development of a personalized system of knowledge representation. In Procedia Computer Science (Vol. 151, pp. 1225–1230). 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