Route Choice Behavior Modeling for Emergency Evacuation and Efficiency Analysis Based on Type-II Fuzzy Theory

For route choice during an outside emergency evacuation, evacuees make different route choice decisions due to their preference diversity. Furthermore, uncertainties of human behavior are inevitable, leading to a high complexity of macroscopic traffic flows and great impact on the evacuation efficiency. In this work, a simulation-based evacuation traffic planning is presented for homogenizing the network traffic flows. In the simulation, the evacuees are divided into two types: panicky and rational ones, and their route choice behavior is captured by two distinct models, respectively. The proportion of panicky evacuees is dynamically changed based on the traffic information level (TIL) and traffic states of downstream links at a decision point. Type-II fuzzy logic system (T2FLS) is used to model the uncertainties of evacuees’ subjective perception on route costs. Comprehensive numerical experiments are done to analyze the impact of TIL, behavior diversity, and the heterogeneity of macroscopic traffic flows on evacuation efficiency. Results show that the proposed evacuation traffic planning is beneficial for improving the evacuation efficiency, alleviating the proportion of panicky evacuees, and homogenizing traffic flows in a large-scale network.