Modeling and simulation of evacuation route choice behavior using fuzzy set theory

Traveler behaviors during emergency evacuation are driven by various factors that are potentially different from those under normal traffic conditions. First, a traveler tends to concern more with the prevailing situation than with long-term interests. Second, both traveler's psychological behaviors and route choice decisions are highly related to the availability and quality of traffic information. Third, evacuation instructions issued by management authorities may also affect the decisions of traveler's route choice. In this paper, evacuation route choice behavior is formulated as the integration of perception behavior on route cost and compliance behavior with the instructed route, which can be taken as the generalized model of the classical logit model. A fuzzy inference system (FIS) is adopted to capture the uncertainty and variability of traveler's perception on route cost by adding a dynamic weight to each link, which takes the level of traffic information and distance from traveler to link as two inputs. Macroscopic simulation framework is proposed to validate the evacuation behavior model using FIS. The case study shows that evacuation efficiency is overestimated by classical logit model, and relative low level and high frequency update of traffic information is recommended. In addition, strong enforcement of traffic management contributes to high evacuation efficiency but fully mandatory management is unnecessary.