An adaptive simulation tool for evacuation scenarios

Daniel Formolo*, C. Natalie van der Wal

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Building useful and efficient models and tools for a varied audience, such as evacuation simulators for scientists, engineers and crisis managers, can be tricky. Even good models can fail in providing information when the user’s tools for the model are scarce of resources. The aim of this work is to propose a new tool that covers the most required features in evacuation scenarios. This paper starts with a review of current software, prototypes and models simulating evacuation scenarios, by discussing their required and desired features. Based on this overview, we propose our simulator comparing it with other models and commercial tools. Moreover, we discuss the importance of building simulators that cover the minimum requirements to avoid the risk of building inefficient models or tools that do not provide enough insights for users to take right decisions in terms of security policies in crowded events. The implications of this work are to present a new simulation tool and to start a discussion in this research field on mandatory features of evacuation simulation tools that will provide valuable information to users and to find out what the criteria are to define these features.

Original languageEnglish
Title of host publicationProgress in Artificial Intelligence - 18th EPIA Conference on Artificial Intelligence, EPIA 2017, Proceedings
PublisherSpringer/Verlag
Pages766-777
Number of pages12
Volume10423 LNAI
ISBN (Print)9783319653396
DOIs
Publication statusPublished - 2017
Event18th EPIA Conference on Artificial Intelligence, EPIA 2017 - Porto, Portugal
Duration: 5 Sept 20178 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10423 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference18th EPIA Conference on Artificial Intelligence, EPIA 2017
Country/TerritoryPortugal
CityPorto
Period5/09/178/09/17

Funding

Acknowledgments. This research was undertaken as part of the EU HORIZON 2020 Project IMPACT (GA 653383) and Science without Borders – CNPq (scholarship reference: 233883/2014-2). We would like to thank our Consortium Partners and stakeholders for their input and the Brazilian Government.

FundersFunder number
Horizon 2020 Framework Programme
Conselho Nacional de Desenvolvimento Científico e Tecnológico233883/2014-2
Horizon 2020653383

    Keywords

    • Crowd model
    • Evacuation
    • Multi-agent
    • Simulation
    • Tools

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