A Schedule-based User Equilibrium Traffic Assignment Model

Equilibrium traffic assignment models exist to deal with a range of observational uncertainties. Perhaps the most well known is the stochastic user equilibrium model, incorporating random perceptual terms to represent components of drivers’ disutility that are not explained through observed attributes (Sheffi, 1985). The uncertainty represented by such a model is from the viewpoint of the modeller; it provides no hypothesis as to how the drivers in the network might themselves consider uncertainty. This latter point is the focus of the present paper. In the context of traffic assignment, the primary source of uncertainty for the individual driver is surely the fact that for any particular trip, the driver will not know in advance the precise traffic conditions he/she would encounter on the alternative routes available. This uncertainty derives from the ambient trip-to-trip variation in travel times, both within and between days, due to factors such as incidents, breakdowns, weather and the variability in activity patterns. These factors lead to variations in, among other things, flows and capacities, which in turn impact on travel times.