Communities detection algorithm to minimize risk during an evacuation

Recent dramatic events recall to the world that is has to deal with risk problematic. Thus, to face risk in an agglomeration, we study hazards from natural or anthropic origin. One problem is to decide if it is necessary to evacuate or confine population. To help decision makers, we analyze the road network structure which may influence flow fluidity especially in a dangerous case. In this work, we detail an algorithm to detect communities in large graphs. It allows to identify routes that may cause problems in an evacuation case. Thanks to this algorithm, we study a toxic cloud propagation in a given zone and identify roads to avoid when evacuating this zone.