An Alternative Stochastic User Equilibrium Formulation Based on Regret Theory

Traffic assignment is the last stage of the classical transportation planning process in which, the travel demand of each O-D pair is allocated to the network links, and links' flows are estimated. To solve such a problem, some assumptions should be made about travellers' decision-making behavior. One of the most popular approaches in this regard is the deterministic assignment that assumes all drivers are fully informed about the condition of the network and they always select the best (usually the shortest) route. These assumptions do not thoroughly match to the reality. To deal with this problem, the concept of stochastic user equilibrium has been introduced. The conventional stochastic user equilibrium assignments models are typically based on random utility theory. In this paper an alternative approach for stochastic user equilibrium assignment called random regret theory has been used in which a random regret-minimization (RRM) model is developed. RRM considers the regret of an option just with respect to outperformed options and furthermore does not lead to a closed-form stochastic user equilibrium (SUE) model, though based on that a formulation of SUE is proposed in a variational inequality form. In this study the definition of regret is modified and based on that a closed form SUE model is developed. This model is examined by two network examples.