Traffic Adaptive Control Framework for Real Time Large-Scale 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 urgently needs to look for ways to control the evacuation traffic flow efficiently and effectively in real-time. This paper, on the foundation of adaptive control theory, puts forward a traffic adaptive control framework for real time large-scale emergency evacuation, the characteristic of which integrates a method of prescriptive reference model and the adaptive control system. The prescriptive reference model is applied to specify, in a short-term and rolling-horizon manner, the desired traffic states, which serves as a reference point for the adaptive control. And the adaptive control system combines these desired states and the current prevailing traffic conditions collected by the sensing system to produce real time traffic control schemes. These traffic control schemes are implemented in the field to guide the real world traffic flow to evolve towards the desired states.