An agent-based evacuation model with social contagion mechanisms and cultural factors

C. Natalie van der Wal, Daniel Formolo, Tibor Bosse

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

© Springer International Publishing AG 2017. A fire incident at a transport hub can cost many lives. To save lives, effective crisis management and prevention measures need to be taken. In this project, the effect of cultural factors in managing and preventing emergencies in public transport systems is analysed. An agent–based model of an evacuating crowd was created. Socio-cultural factors that were modelled are: familiarity with environment, response time and social contagion of fear and beliefs about the situation. Simulation results show that (1) familiarity and social contagion decrease evacuation time, while increasing the number of falls; (2) crowd density and social contagion increase evacuation time and falls. All three factors show different effects on the response time. This model will be used by transport operators to estimate the effect of these socio-cultural factors and prepare for emergencies.
LanguageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer/Verlag
Pages620-627
Number of pages8
ISBN (Print)9783319600413
DOIs
StatePublished - 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10350 LNCS

Cite this

van der Wal, C. N., Formolo, D., & Bosse, T. (2017). An agent-based evacuation model with social contagion mechanisms and cultural factors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 620-627). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10350 LNCS). Springer/Verlag. DOI: 10.1007/978-3-319-60042-0_68
van der Wal, C. Natalie ; Formolo, Daniel ; Bosse, Tibor. / An agent-based evacuation model with social contagion mechanisms and cultural factors. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer/Verlag, 2017. pp. 620-627 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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van der Wal, CN, Formolo, D & Bosse, T 2017, An agent-based evacuation model with social contagion mechanisms and cultural factors. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10350 LNCS, Springer/Verlag, pp. 620-627. DOI: 10.1007/978-3-319-60042-0_68

An agent-based evacuation model with social contagion mechanisms and cultural factors. / van der Wal, C. Natalie; Formolo, Daniel; Bosse, Tibor.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer/Verlag, 2017. p. 620-627 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10350 LNCS).

Research output: Chapter in Book/Report/Conference proceedingChapter

TY - CHAP

T1 - An agent-based evacuation model with social contagion mechanisms and cultural factors

AU - van der Wal,C. Natalie

AU - Formolo,Daniel

AU - Bosse,Tibor

PY - 2017

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N2 - © Springer International Publishing AG 2017. A fire incident at a transport hub can cost many lives. To save lives, effective crisis management and prevention measures need to be taken. In this project, the effect of cultural factors in managing and preventing emergencies in public transport systems is analysed. An agent–based model of an evacuating crowd was created. Socio-cultural factors that were modelled are: familiarity with environment, response time and social contagion of fear and beliefs about the situation. Simulation results show that (1) familiarity and social contagion decrease evacuation time, while increasing the number of falls; (2) crowd density and social contagion increase evacuation time and falls. All three factors show different effects on the response time. This model will be used by transport operators to estimate the effect of these socio-cultural factors and prepare for emergencies.

AB - © Springer International Publishing AG 2017. A fire incident at a transport hub can cost many lives. To save lives, effective crisis management and prevention measures need to be taken. In this project, the effect of cultural factors in managing and preventing emergencies in public transport systems is analysed. An agent–based model of an evacuating crowd was created. Socio-cultural factors that were modelled are: familiarity with environment, response time and social contagion of fear and beliefs about the situation. Simulation results show that (1) familiarity and social contagion decrease evacuation time, while increasing the number of falls; (2) crowd density and social contagion increase evacuation time and falls. All three factors show different effects on the response time. This model will be used by transport operators to estimate the effect of these socio-cultural factors and prepare for emergencies.

KW - Crowd model

KW - Evacuation simulation

KW - Social contagion

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DO - 10.1007/978-3-319-60042-0_68

M3 - Chapter

SN - 9783319600413

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 620

EP - 627

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer/Verlag

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van der Wal CN, Formolo D, Bosse T. An agent-based evacuation model with social contagion mechanisms and cultural factors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer/Verlag. 2017. p. 620-627. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Available from, DOI: 10.1007/978-3-319-60042-0_68