Perception updating and day-to-day travel choice dynamics in traffic networks with information provision

A Bayesian updating model is developed to capture the mechanism by which tr avelers update their travel time perceptions from one day to the next in li ght of information provided by Advanced Traveler Information Systems (ATIS) and their previous experience. The availability and perceived quality of t raffic information are explicitly modeled within the proposed framework. Th e uncertainty associated with a driver's travel time estimate is modeled in a stochastic dynamic framework and is incorporated in a travel choice mode l. Each driver uses a disutility function of perceived travel time and perc eived schedule delay to evaluate the alternative travel choices, then selec ts an alternative based on the utility maximization principle. The percepti on updating model and the choice model are integrated with a dynamic traffi c simulator (DYNASMART). Empirical results from the simulation experiments and their implications are also presented. (C) 1998 Elsevier Science Ltd. A ll rights reserved.