A Stochastic Dynamic Traffic Assignment Model for Emergency Evacuations That Considers Background Traffic

Abstract

In this work, we present a stochastic dynamic traffic assignment model for emergency evacuations that considers background traffic. First, the equilibrium functions of the entry time and path choice are formulated based on the logit model. The constraints of this formulation include the state equation, propagation function, and conservation. The proposed equilibrium functions are formulated as a variational inequality problem, which is solved by the dynamic traffic network demand loading iterative method. Based on a case study in Wenling, China, we verify the proposed model on the basis of iterative evolution, path assignment, and model comparison. In addition, we perform sensitivity analysis of four relevant parameters, namely, the length of the time interval, total number of evacuation vehicles, perception error parameters of the total travel cost, and path travel cost. The results make it evident that the proposed model assists evacuation planners to effectively understand real-time dynamic changes of evacuation vehicles and the influence of background vehicles and to generate optimal emergency plans.