Traditionally, the value of travel time savings (VTTS) and the value of reliability (or reduced variability) are estimated within a linear utility functional form, which assumes risk-neutral attitudes for decision makers. In this paper, the authors develop non-linear 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. The authors also investigate unobserved between-individual heterogeneity in time-related parameters and risk attitudes using a mixed multinomial logit (MMNL) model. More importantly, the willingness to pay values was calculated for reducing the mean travel time and variability (earlier/later than the preferred arrival time) within the non-linear scheduling framework. This 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 non-linear scheduling model predicts earlier optimal departure times than the traditional linear scheduling model. Some important issues related to modelling non-linearity are also discussed. (Author/publisher)
Samenvatting