A Mixed Equilibrium Dynamic Traffic Flow Evolution Model with Capacity Constraint

Abstract

This paper analyzes the network flow adjustment process under a capacity constraint where the market penetration of advanced traveler information system (ATIS) was predefined. It was assumed that the travelers influenced by ATIS follow two types of behavior rules while choosing the route: the one equipped with ATIS would select the shortest path, and obeyed the user equilibrium (UE) distribution; while the other unequipped with ATIS would choose the path according to their perceived travel time, and obeyed the Logit random distribution. A discrete mixed behavior route flow dynamic evolution model with a capacity constraint has been established, whose equilibrium state is equivalent to a minimized problem's Karush-Kuhn-Tucker (KT) condition. To analyze the proposed model, a numerical example was conducted. The results show that the proposed models converged to the mixed equilibrium state.