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PSO-based evacuation simulation framework
Evacuation simulation is a critical and important research issue for people to design safer building layouts or plan more effective evacuation routes. Many studies adopted methodologies in evolutionary computation into the evacuation simulation systems for finding better solutions. To simulate human...
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creator | Pei-Chuan Tsai Chih-Ming Chen Ying-ping Chen |
description | Evacuation simulation is a critical and important research issue for people to design safer building layouts or plan more effective evacuation routes. Many studies adopted methodologies in evolutionary computation into the evacuation simulation systems for finding better solutions. To simulate human behavior or crowd motion is one key factor to the practicality of the system. Particle swarm optimization algorithm (PSO), which is originated from the inspiration of bird flocking, is commonly applied to model human behavior. Based on the PSO-based human behavior simulation, many studies have got good results on evacuation simulation. However, the configurations of describing the experiment environment in the literature are complicated and specialized for certain specific scenarios. Observing the fact, we propose a new PSO-based simulation framework in order to provide a simple and general way to configure various simulation scenarios. This work adopts our previously proposed PSO-based crowd movement controlling mechanism and introduces new mechanisms to make the simulation fitting into evacuation circumstance more real. In the proposed framework, all people, obstacles, exits, and even the evacuation guide indicators are modeled as the original component of the PSO algorithm. It is convenient to setup the simulation environment upon the framework. Therefore, taking the proposed work as a research tool will be advantageous when the issue of evacuation simulation is investigated. |
doi_str_mv | 10.1109/CEC.2014.6900600 |
format | conference_proceeding |
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Many studies adopted methodologies in evolutionary computation into the evacuation simulation systems for finding better solutions. To simulate human behavior or crowd motion is one key factor to the practicality of the system. Particle swarm optimization algorithm (PSO), which is originated from the inspiration of bird flocking, is commonly applied to model human behavior. Based on the PSO-based human behavior simulation, many studies have got good results on evacuation simulation. However, the configurations of describing the experiment environment in the literature are complicated and specialized for certain specific scenarios. Observing the fact, we propose a new PSO-based simulation framework in order to provide a simple and general way to configure various simulation scenarios. This work adopts our previously proposed PSO-based crowd movement controlling mechanism and introduces new mechanisms to make the simulation fitting into evacuation circumstance more real. In the proposed framework, all people, obstacles, exits, and even the evacuation guide indicators are modeled as the original component of the PSO algorithm. It is convenient to setup the simulation environment upon the framework. Therefore, taking the proposed work as a research tool will be advantageous when the issue of evacuation simulation is investigated.</description><identifier>ISSN: 1089-778X</identifier><identifier>EISSN: 1941-0026</identifier><identifier>EISBN: 9781479914883</identifier><identifier>EISBN: 1479966266</identifier><identifier>EISBN: 9781479966264</identifier><identifier>EISBN: 1479914886</identifier><identifier>DOI: 10.1109/CEC.2014.6900600</identifier><language>eng</language><publisher>IEEE</publisher><subject>Buildings ; Collision avoidance ; Computational modeling ; Layout ; Linear programming ; Particle swarm optimization</subject><ispartof>2014 IEEE Congress on Evolutionary Computation (CEC), 2014, p.1944-1950</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6900600$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54796,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6900600$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Pei-Chuan Tsai</creatorcontrib><creatorcontrib>Chih-Ming Chen</creatorcontrib><creatorcontrib>Ying-ping Chen</creatorcontrib><title>PSO-based evacuation simulation framework</title><title>2014 IEEE Congress on Evolutionary Computation (CEC)</title><addtitle>CEC</addtitle><description>Evacuation simulation is a critical and important research issue for people to design safer building layouts or plan more effective evacuation routes. 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In the proposed framework, all people, obstacles, exits, and even the evacuation guide indicators are modeled as the original component of the PSO algorithm. It is convenient to setup the simulation environment upon the framework. Therefore, taking the proposed work as a research tool will be advantageous when the issue of evacuation simulation is investigated.</description><subject>Buildings</subject><subject>Collision avoidance</subject><subject>Computational modeling</subject><subject>Layout</subject><subject>Linear programming</subject><subject>Particle swarm optimization</subject><issn>1089-778X</issn><issn>1941-0026</issn><isbn>9781479914883</isbn><isbn>1479966266</isbn><isbn>9781479966264</isbn><isbn>1479914886</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2014</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj89Lw0AQRldRsNTcBS-9etg4k93N7Bwl1B9QqKCCt7LJzkK0sZK0lv73BtrT9w6PB59SNwg5IvB9Na_yAtDmJQOUAGcqY_JoiRmt9-ZcTZAtaoCivBgZPGsi_3mlsmH4AgAkcs7iRN29vi11HQaJM_kLzS5s283PbGi73fqIqQ-d7Df997W6TGE9SHbaqfp4nL9Xz3qxfHqpHha6RXJbHUWYCmdNSlQSQ7TQRGzYesaiCU2qa5fQG0yjUkMRJdVuFA0760mimarbY7cVkdVv33ahP6xOR80_07VDog</recordid><startdate>201407</startdate><enddate>201407</enddate><creator>Pei-Chuan Tsai</creator><creator>Chih-Ming Chen</creator><creator>Ying-ping Chen</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201407</creationdate><title>PSO-based evacuation simulation framework</title><author>Pei-Chuan Tsai ; Chih-Ming Chen ; Ying-ping Chen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-dee972543ff76790d40cd1c948912cacfbb5f1831f43fb02defb5679395487ed3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Buildings</topic><topic>Collision avoidance</topic><topic>Computational modeling</topic><topic>Layout</topic><topic>Linear programming</topic><topic>Particle swarm optimization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pei-Chuan Tsai</creatorcontrib><creatorcontrib>Chih-Ming Chen</creatorcontrib><creatorcontrib>Ying-ping Chen</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Pei-Chuan Tsai</au><au>Chih-Ming Chen</au><au>Ying-ping Chen</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>PSO-based evacuation simulation framework</atitle><btitle>2014 IEEE Congress on Evolutionary Computation (CEC)</btitle><stitle>CEC</stitle><date>2014-07</date><risdate>2014</risdate><spage>1944</spage><epage>1950</epage><pages>1944-1950</pages><issn>1089-778X</issn><eissn>1941-0026</eissn><eisbn>9781479914883</eisbn><eisbn>1479966266</eisbn><eisbn>9781479966264</eisbn><eisbn>1479914886</eisbn><abstract>Evacuation simulation is a critical and important research issue for people to design safer building layouts or plan more effective evacuation routes. Many studies adopted methodologies in evolutionary computation into the evacuation simulation systems for finding better solutions. To simulate human behavior or crowd motion is one key factor to the practicality of the system. Particle swarm optimization algorithm (PSO), which is originated from the inspiration of bird flocking, is commonly applied to model human behavior. Based on the PSO-based human behavior simulation, many studies have got good results on evacuation simulation. However, the configurations of describing the experiment environment in the literature are complicated and specialized for certain specific scenarios. Observing the fact, we propose a new PSO-based simulation framework in order to provide a simple and general way to configure various simulation scenarios. This work adopts our previously proposed PSO-based crowd movement controlling mechanism and introduces new mechanisms to make the simulation fitting into evacuation circumstance more real. In the proposed framework, all people, obstacles, exits, and even the evacuation guide indicators are modeled as the original component of the PSO algorithm. It is convenient to setup the simulation environment upon the framework. Therefore, taking the proposed work as a research tool will be advantageous when the issue of evacuation simulation is investigated.</abstract><pub>IEEE</pub><doi>10.1109/CEC.2014.6900600</doi><tpages>7</tpages></addata></record> |
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ispartof | 2014 IEEE Congress on Evolutionary Computation (CEC), 2014, p.1944-1950 |
issn | 1089-778X 1941-0026 |
language | eng |
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source | IEEE Xplore All Conference Series |
subjects | Buildings Collision avoidance Computational modeling Layout Linear programming Particle swarm optimization |
title | PSO-based evacuation simulation framework |
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