Understanding the dynamics of individual travel choice behavior is both a considerable research challenge and of considerable practical importance. Of particular interest are the day-to-day dynamics of commuters? route and departure time choice decisions, since these processes influence peak period conditions. Two of the key mechanisms underlying these behavioral dynamics are the process by which commuters update their perceptions of network travel times (which we shall refer to as learning) and the process by which they adjust their behavior as a result of this learning. This paper presents a framework for modeling the day-to-day dynamics of drivers? route and departure time choice decisions in a commuting context and presents recent estimation results based on data collected in a series of web-based experiments involving travelers making repeated decisions in a hypothetical two-route network over a period of 15 simulated days. The estimation results indicate that triggering, updating and adaptation are indeed distinct processes and that the proposed framework constitutes a fruitful direction for future research.
Samenvatting