Abstract

In traditional travel time reliability valuation studies, the value of travel time savings and the value of travel time reliability (or reduced time variability) are estimated within a linear utility functional form, which assumes risk-neutral attitudes for decision makers. In this paper, we develop nonlinear scheduling models to address both risk attitude and preference in the context of a stated choice experiment of car commuters facing risky choices where the risk is associated with the trip time. We also investigate unobserved betweenindividual heterogeneity in time-related parameters and risk attitudes using a mixed multinomial logit model. The willingness-to-pay values for reducing the mean travel time and variability (earlier/later than the preferred arrival time) are also estimated within the nonlinear scheduling framework. The model is then used to estimate preferred departure times for commuters, assuming that random link capacities are the source of travel time variability. Results show that the more variable travel times are, the earlier commuters depart and that the nonlinear scheduling model predicts earlier optimal departure times than the linear scheduling model does. The application in this paper helps to bridge the gap between theory and practice. © 2012 INFORMS.