MODELING OF THE VULNERABILITY RELATED TO THE DYNAMIC ROAD TRAFFIC
Identifieur interne : 000E74 ( Main/Exploration ); précédent : 000E73; suivant : 000E75MODELING OF THE VULNERABILITY RELATED TO THE DYNAMIC ROAD TRAFFIC
Auteurs : Cyrille Bertelle [France] ; Antoine Dutot [France] ; Michel Nabaa [France] ; Damien Olivier [France] ; Pascal Mallet [France]Source :
English descriptors
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Abstract
The utilization of the road network by vehicles with different behaviors can generate a danger under normal and especially under evacuation situations. In Le Havre agglomeration (CODAH), there are 33 establishments classified SEVESO with high threshold. The modeling and assessment of the danger is useful when it intersects with the exposed stakes. The most important factor is people. In the literature, vulnerability maps are constructed to help decision makers assess the risk. These maps are based on several types of vulnerability: socio-demographic, biophysical and other different types of hazards. Nevertheless, such approaches remain static and do not take into account the population displacement in the estimation of the vulnerability. We propose a decision support system which consists in a dynamic vulnerability map based on the difficulty to evacuate different sectors in Le Havre agglomeration. This map is visualized using the Geographic Information System (GIS) of the CODAH and evolves according to the dynamic state of the road traffic through a detection of communities in a large graph. This detection is realized by an ant algorithm.
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Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Hal, to step Corpus: 000206
- to stream Hal, to step Curation: 000206
- to stream Hal, to step Checkpoint: 000619
- to stream Main, to step Merge: 000E89
- to stream Main, to step Curation: 000E74
Le document en format XML
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<desc><address><addrLine>Avenue de l'Université UFR des Sciences et Techniques 76800 Saint-Etienne du Rouvray</addrLine>
<country key="FR"></country>
</address>
<ref type="url">http://www.litislab.eu</ref>
</desc>
<listRelation><relation active="#struct-300317" type="direct"></relation>
<relation name="EA4108" active="#struct-300318" type="direct"></relation>
<relation active="#struct-301288" type="direct"></relation>
<relation active="#struct-301232" type="indirect"></relation>
</listRelation>
<tutelles><tutelle active="#struct-300317" type="direct"><org type="institution" xml:id="struct-300317" status="VALID"><orgName>Université du Havre</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
<tutelle name="EA4108" active="#struct-300318" type="direct"><org type="institution" xml:id="struct-300318" status="VALID"><orgName>Université de Rouen</orgName>
<desc><address><addrLine> 1 rue Thomas Becket - 76821 Mont-Saint-Aignan</addrLine>
<country key="FR"></country>
</address>
<ref type="url">http://www.univ-rouen.fr/</ref>
</desc>
</org>
</tutelle>
<tutelle active="#struct-301288" type="direct"><org type="department" xml:id="struct-301288" status="VALID"><orgName>Institut National des Sciences Appliquées - Rouen</orgName>
<orgName type="acronym">INSA Rouen</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
<listRelation><relation active="#struct-301232" type="direct"></relation>
</listRelation>
</org>
</tutelle>
<tutelle active="#struct-301232" type="indirect"><org type="institution" xml:id="struct-301232" status="VALID"><orgName>Institut National des Sciences Appliquées</orgName>
<orgName type="acronym">INSA</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>France</country>
<placeName><settlement type="city">Le Havre</settlement>
<region type="region" nuts="2">Région Normandie</region>
<region type="old region" nuts="2">Haute-Normandie</region>
</placeName>
<orgName type="university">Université du Havre</orgName>
<placeName><settlement type="city">Rouen</settlement>
<region type="region" nuts="2">Région Normandie</region>
<region type="old region" nuts="2">Haute-Normandie</region>
</placeName>
<orgName type="university">Université de Rouen</orgName>
</affiliation>
</author>
<author><name sortKey="Mallet, Pascal" sort="Mallet, Pascal" uniqKey="Mallet P" first="Pascal" last="Mallet">Pascal Mallet</name>
<affiliation wicri:level="1"><hal:affiliation type="laboratory" xml:id="struct-103905" status="INCOMING"><orgName>CODAH</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
<listRelation><relation active="#struct-324942" type="direct"></relation>
</listRelation>
<tutelles><tutelle active="#struct-324942" type="direct"><org type="institution" xml:id="struct-324942" status="INCOMING"><orgName>COmmunauté de l'Agglomération Havraise</orgName>
<desc><address><country key="FR"></country>
</address>
</desc>
</org>
</tutelle>
</tutelles>
</hal:affiliation>
<country>France</country>
</affiliation>
</author>
</analytic>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Communities Detection</term>
<term>Decision Support System</term>
<term>Dynamic Graph</term>
<term>Dynamic Vulnerability Map</term>
<term>GIS</term>
<term>Risk</term>
<term>Self-Organization</term>
<term>Traffic Flow</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">The utilization of the road network by vehicles with different behaviors can generate a danger under normal and especially under evacuation situations. In Le Havre agglomeration (CODAH), there are 33 establishments classified SEVESO with high threshold. The modeling and assessment of the danger is useful when it intersects with the exposed stakes. The most important factor is people. In the literature, vulnerability maps are constructed to help decision makers assess the risk. These maps are based on several types of vulnerability: socio-demographic, biophysical and other different types of hazards. Nevertheless, such approaches remain static and do not take into account the population displacement in the estimation of the vulnerability. We propose a decision support system which consists in a dynamic vulnerability map based on the difficulty to evacuate different sectors in Le Havre agglomeration. This map is visualized using the Geographic Information System (GIS) of the CODAH and evolves according to the dynamic state of the road traffic through a detection of communities in a large graph. This detection is realized by an ant algorithm.</div>
</front>
</TEI>
<affiliations><list><country><li>France</li>
</country>
<region><li>Haute-Normandie</li>
<li>Région Normandie</li>
</region>
<settlement><li>Le Havre</li>
<li>Rouen</li>
</settlement>
<orgName><li>Université de Rouen</li>
<li>Université du Havre</li>
</orgName>
</list>
<tree><country name="France"><region name="Région Normandie"><name sortKey="Bertelle, Cyrille" sort="Bertelle, Cyrille" uniqKey="Bertelle C" first="Cyrille" last="Bertelle">Cyrille Bertelle</name>
</region>
<name sortKey="Dutot, Antoine" sort="Dutot, Antoine" uniqKey="Dutot A" first="Antoine" last="Dutot">Antoine Dutot</name>
<name sortKey="Mallet, Pascal" sort="Mallet, Pascal" uniqKey="Mallet P" first="Pascal" last="Mallet">Pascal Mallet</name>
<name sortKey="Nabaa, Michel" sort="Nabaa, Michel" uniqKey="Nabaa M" first="Michel" last="Nabaa">Michel Nabaa</name>
<name sortKey="Olivier, Damien" sort="Olivier, Damien" uniqKey="Olivier D" first="Damien" last="Olivier">Damien Olivier</name>
</country>
</tree>
</affiliations>
</record>
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