Modeling of the Vulnerability Related to the Dynamic Road Traffic

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.