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Real time traffic control framework based on simulated human intelligence for emergency evacuation
Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population...
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creator | Guiyan Jiang Zhengyan Wu Chunqin Zhang Qiao Li |
description | Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on real-time efficient traffic control method for emergency evacuation. This paper, on the foundation of simulated human intelligent control, puts forward a framework of real-time traffic control for emergency evacuation, the characteristic of which integrates a method of feature information acquisition and processing, characteristic pattern set, pattern recognition and control rule set. The work of this paper attempts to optimize the real-time traffic control method in terms of both quality and feasibility. |
doi_str_mv | 10.1109/WCICA.2010.5554888 |
format | conference_proceeding |
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Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on real-time efficient traffic control method for emergency evacuation. This paper, on the foundation of simulated human intelligent control, puts forward a framework of real-time traffic control for emergency evacuation, the characteristic of which integrates a method of feature information acquisition and processing, characteristic pattern set, pattern recognition and control rule set. The work of this paper attempts to optimize the real-time traffic control method in terms of both quality and feasibility.</description><identifier>EISBN: 9781424467129</identifier><identifier>EISBN: 142446711X</identifier><identifier>EISBN: 9781424467112</identifier><identifier>EISBN: 1424467128</identifier><identifier>DOI: 10.1109/WCICA.2010.5554888</identifier><language>eng</language><publisher>IEEE</publisher><subject>Artificial neural networks ; Cognition ; emergency evacuation ; engineering of communications and transportation system ; Humans ; Intelligent control ; intelligent control system ; Real time systems ; real-time ; Roads ; simulated human ; Traffic control</subject><ispartof>2010 8th World Congress on Intelligent Control and Automation, 2010, p.5196-5200</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5554888$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5554888$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Guiyan Jiang</creatorcontrib><creatorcontrib>Zhengyan Wu</creatorcontrib><creatorcontrib>Chunqin Zhang</creatorcontrib><creatorcontrib>Qiao Li</creatorcontrib><title>Real time traffic control framework based on simulated human intelligence for emergency evacuation</title><title>2010 8th World Congress on Intelligent Control and Automation</title><addtitle>WCICA</addtitle><description>Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on real-time efficient traffic control method for emergency evacuation. This paper, on the foundation of simulated human intelligent control, puts forward a framework of real-time traffic control for emergency evacuation, the characteristic of which integrates a method of feature information acquisition and processing, characteristic pattern set, pattern recognition and control rule set. The work of this paper attempts to optimize the real-time traffic control method in terms of both quality and feasibility.</description><subject>Artificial neural networks</subject><subject>Cognition</subject><subject>emergency evacuation</subject><subject>engineering of communications and transportation system</subject><subject>Humans</subject><subject>Intelligent control</subject><subject>intelligent control system</subject><subject>Real time systems</subject><subject>real-time</subject><subject>Roads</subject><subject>simulated human</subject><subject>Traffic control</subject><isbn>9781424467129</isbn><isbn>142446711X</isbn><isbn>9781424467112</isbn><isbn>1424467128</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNot0M1KxDAUBeC4EJSxL6CbvEDHJE2adCnFPxgQRHE53CQ3Gk1bSVNl3t6RmdXh2xwOh5BLztacs-76rX_sb9aC7a2UksaYE1J12nAppGw1F90Zqeb5kzHGdduKVpwT-4yQaIkD0pIhhOiom8aSp0RDhgF_p_xFLczo6TTSOQ5LgrLHxzLASONYMKX4jqNDGqZMccD8rx3FH3ALlDiNF-Q0QJqxOuaKvN7dvvQP9ebpfj94U0euVamtAtd02jorg2fSBA_KYRuAB9ZwBwwaI5Xx2hqhZHBWCMdV24EVGMD7ZkWuDr0REbffOQ6Qd9vjE80f5QBXXg</recordid><startdate>201007</startdate><enddate>201007</enddate><creator>Guiyan Jiang</creator><creator>Zhengyan Wu</creator><creator>Chunqin Zhang</creator><creator>Qiao Li</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201007</creationdate><title>Real time traffic control framework based on simulated human intelligence for emergency evacuation</title><author>Guiyan Jiang ; Zhengyan Wu ; Chunqin Zhang ; Qiao Li</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-b5ac397bcb4fd048fda5ce6fa1f031ca0a38458d7b8254fcb22c1569ab2efadd3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Artificial neural networks</topic><topic>Cognition</topic><topic>emergency evacuation</topic><topic>engineering of communications and transportation system</topic><topic>Humans</topic><topic>Intelligent control</topic><topic>intelligent control system</topic><topic>Real time systems</topic><topic>real-time</topic><topic>Roads</topic><topic>simulated human</topic><topic>Traffic control</topic><toplevel>online_resources</toplevel><creatorcontrib>Guiyan Jiang</creatorcontrib><creatorcontrib>Zhengyan Wu</creatorcontrib><creatorcontrib>Chunqin Zhang</creatorcontrib><creatorcontrib>Qiao Li</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 Electronic Library (IEL)</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>Guiyan Jiang</au><au>Zhengyan Wu</au><au>Chunqin Zhang</au><au>Qiao Li</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Real time traffic control framework based on simulated human intelligence for emergency evacuation</atitle><btitle>2010 8th World Congress on Intelligent Control and Automation</btitle><stitle>WCICA</stitle><date>2010-07</date><risdate>2010</risdate><spage>5196</spage><epage>5200</epage><pages>5196-5200</pages><eisbn>9781424467129</eisbn><eisbn>142446711X</eisbn><eisbn>9781424467112</eisbn><eisbn>1424467128</eisbn><abstract>Large-scale natural or man-made disasters have the potential to cause great loss of life, human injury and extreme property damage. Evacuation from areas at risk is often one of the most feasible strategies that can be undertaken in response to these types of disasters. Evacuating a large population in the shortest possible time is an extremely complicated and difficult task, which primarily relies on real-time efficient traffic control method for emergency evacuation. This paper, on the foundation of simulated human intelligent control, puts forward a framework of real-time traffic control for emergency evacuation, the characteristic of which integrates a method of feature information acquisition and processing, characteristic pattern set, pattern recognition and control rule set. The work of this paper attempts to optimize the real-time traffic control method in terms of both quality and feasibility.</abstract><pub>IEEE</pub><doi>10.1109/WCICA.2010.5554888</doi><tpages>5</tpages></addata></record> |
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identifier | EISBN: 9781424467129 |
ispartof | 2010 8th World Congress on Intelligent Control and Automation, 2010, p.5196-5200 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Artificial neural networks Cognition emergency evacuation engineering of communications and transportation system Humans Intelligent control intelligent control system Real time systems real-time Roads simulated human Traffic control |
title | Real time traffic control framework based on simulated human intelligence for emergency evacuation |
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