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Previous work on the effect of advanced traveler information systems was concerned primarily with immediate route choice decisions in response to real-time traffic information. Real-time traffic information also influences day-to-day decisions of trip makers, including departure time and route choices. Joint departure time decision and pretrip route selection are addressed, as well as en route path switching behavior by commuters under real-time information availability. Data were used from laboratory experiments using a dynamic interactive traveler simulator that allows actual commuters to simultaneously interact with each other within a simulated traffic corridor. Given real-time information provided by the system, commuters determine their departure time and route at the origin and select paths en route at various decision nodes along the trip. Day-to-day dynamic models of commuters’ joint departure time and route switching decisions are developed and calibrated by using a multinomial probit model framework that takes into account commuters’ learning from experience. The analysis provides insight into day-to-day effects of real-time traffic information on user decisions. Results indicate that the reliability of real-time information and supplied schedule delay (relative to the commuters’ preferred arrival time) are significant variables that influence users’ indifference band governing route switching behavior both pretrip and en route. These models are intended for use within evaluation frameworks (e.g., simulation-assignment models). In addition, the substantive insights provide guidelines for the design of real-time information content and systems.
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