Traffic Assignment With Adaptive Routing Choices in Stochastic Time-Dependent Networks

This paper establishes a user equilibrium Dynamic Traffic Assignment (DTA) model where users make adaptive routing choices in a stochastic time-dependent network. Travel times on all links at all discrete times are jointly distributed random variables whose distribution is endogenous to the DTA model. A traveler is assumed to know a priori the joint distribution, and during a trip s/he has access to online information on realized link travel times based on which a decision on what node to take next is made. Such a traveler is said to follow a routing policy, defined as a mapping from all possible states to next nodes to take, where a state is a triple of node, time and online information.