Congestion, Stochastic, and Similarity Effects in Stochastic: User-Equilibrium Models

Different effects in stochastic user-equilibrium formulations are compared. The starting point is the logit assignment formulation for the stochastic user-equilibrium model. Recently, extended logit-based models were developed as solutions of equivalent stochastic user-equilibrium problems. These extended logit models are theoretically superior to the simple logit model, because they take into account the similarity among routes. The similarity indexes were defined based on physical parameters of the network, such as link lengths, and therefore did not depend on congestion. The assumption that similarity coefficients are independent of congestion means that the similarity effect and the congestion effect are treated separately. However, both similarity and congestion effects are taken into account in the equilibrium formulations. Simple network examples are presented to illustrate the sensitivity of the link flow pattern (and path flow pattern) to the three different effects in stochastic assignment models: the congestion effect, the stochastic effect, and the similarity effect. The relative influence of those effects on the flow patterns is discussed.