Emergency Response Plans Assessment Based on Stochastic Markov Traffic Flow Model

To evaluate and optimize the evacuation plan in the emergency planning is the key problem of the optimization and assessment of emergency plan. This paper focused on the how to model the crowd evacuation process with the characteristics of dynamic spatial-temporal distribution, which minimize the human exposure risk (death or casualties). A discrete state stochastic Markov process was used to simulate the movement of the evacuees in this paper. The study area was divided into nodes with different shape and size; the links that connected the nodes were used to represent the road network in the area. Transition from node-to-node was simulated as a random process where the probability of transition depended on the dynamically changed states of the destination and origin nodes and also on the link between them. Solution of the Markov process provided the expected distribution of the evacuees in the nodes of the area as a function of time. Then, according to the way how extreme phenomena impact individual and the dose-response relationship, the people's health effects (e.g., death, several kinds of injuries etc.) obtained in the evacuation process can be calculated, so that the accident's health consequence can be determined. Finally, different emergency response policies can be evaluated with corresponding health consequence, so that the emergency policy can be optimized.