Dynamic network modelling of travel guidance impacts

This paper describes network modelling of travel guidance impacts using combined dynamic distribution and assignment (CDDA) in which a subset of area motorists are provided real-time directives as to destination, route, and departure time decisions. Examples illustrate potential magnitudes of system-wide impacts, including travel time and fuel consumption, achieved by different percentages of motorists given directives aimed at improving user equilibrium conditions. Travel guidance regarding modal choice is not included in this paper, although that extension is similar to other network models. Results are given for a Pittsburgh network in which freeway lanes are partially blocked during rush hour due to a truck accident. Indications are that significant reductions in system-wide impacts can be achieved by guiding a subset of area motorists to specific travel choices based on real-time information. Future research issues are types, amounts, and locations of real-time data needed to provide reliable travel guidance, and the relative impacts of in-vehicle versus point-of-departure travel guidance systems.