Impacts of the least perceived travel cost on the Weibit network equilibrium

Abstract

This study investigates the impacts of the least perceived travel cost on the stochastic user equilibrium (SUE) problem. The Weibit SUE models are considered since they have a location parameter that naturally capture the least perceived travel cost. Considering a positive location parameter enhances the behavioral reality by attaching a positive lower-bound to the perceived travel cost distributions. It reduces the perception variances route-specifically and causes route-specific coefficients of variation (CVs). The CVs reduce proportionally slower for shorter routes, thus contributing to resolving the scale insensitivity issue in the Weibit SUE models. In the meantime, the route-specific CVs cause better discrimination between short and long routes in terms of relative variability; more travelers shift to the shortest route between each origin-destination pair. Numerical results confirm the analytical results regarding the effects of the least perceived travel costs and demonstrate the efficiency and robustness of the proposed solution algorithm.

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