Modeling dynamic route choice behavior under uncertainty using concepts of regret and disappointment

The paper reports progress in developing a dynamic disappointment and regret-based route choice model, which incorporates the learning uncertain travel times. Numerical simulations were conducted to measure the effects of varying travel time distributions of available routes, parameters for sensitivity to regret and disappointment, and initial guesses travelers have for the routes’ travel times. Four different simulation scenarios were explored. Among the inputs varied, the interaction between the travel time distribution of the routes and the magnitudes of the parameters for regret and disappointment is what more strongly affected shares. It was found that disappointment averse travelers would prefer routes with lower variability, even if the average travel times were higher. Regret averse travelers, on the other hand, take both mean and variance of the routes into consideration for making decisions, and would prefer routes with higher chances of generating lower outcomes, even if their variabilities were high. It was found an indirect effect of varying the initial priors on the shares. When narrow initial guesses hold learning back, the route may be kept in relative disadvantage (in comparison with concurrent routes), having decreased its chances of being chosen and of having its subjective distribution updated, feeding its position of disadvantage and characterizing a cyclic effect