DAY-TO-DAY DYNAMICS OF COMMUTER ROUTE CHOICE BEHAVIOUR UNDER REAL-TIME INFORMATION

In this paper, the experimental data collected from a dynamic simulator are used to develop a nd calibrate commuter behavior models under a multinomial probit (MNP) model framework. The goal is to take into account travelers' learning from past experience with the system and to gain insights into the day-to-day dynamics of traveler decision process under Advanced Traveler Information Systems (ATIS). A description of the laboratory experiment is presented, followed by framework for the day-to- day commuter route switching models under ATIS. A brief discussion and interpretation of the model specification is then presented. The paper concludes with a discussion of the estimated results.