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 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.