Traffic Equilibrium Assignment for Multiclass Network Based on Similarity Measure

This paper presents a novel user equilibrium traffic assignment model in view of the fuzzy path costs for multiclass transportation network. In the model, drivers are divided into several classes according as their knowledge about the network traffic condition and travel-decision characteristics are the same within each class, but differ among classes. Some new concepts, such as OD perceived cost and familiar level with the traffic condition, are introduced based on a-cut of fuzzy set. The equilibrium principle is defined based on the similarity measure and equilibrium condition is formulated as an equivalent variational inequality problem. A numerical example shows that the proposed model obtains more realistic results than the other two models, UE and SUE.