Building efficient stated choice design for departure time choices using the scheduling model

Theoretical considerations and practical implementations

Abstract

Modelling departure time is an important step in forecasting traffic demand. The purpose of this research is to contribute to the data collection field when studying departure time choices. Differently from the majority of the previous studies we used an efficient stated preference (SP) experiment. The objective in an efficient design is to construct a stated preference experiment which minimizes the standard errors of the estimated parameter in the model. Thus, the benefits of using an efficient design are more robust parameter estimates and/or that it allows using smaller sample sizes. However, building experimental designs for the departure time is challenging for two main reasons: 1) interdependence among attributes, and 2) realism in the choice tasks. To ensure realism, we customized the choice task based on the trips described by each individual in a trip diary and on the departure time needed in order to be at work at their preferred arrival time. However, with efficient designs it is not possible to customize the SP for each individual, unless the real trips are known before optimizing the SP design. To overcome this challenge, six different designs were constructed based on predefined travel times (10, 20, 30, 40, 50, and 60 minutes). Respondents were presented with the design which was closest to their reported travel time in the trip diary. The design was simulated using almost 20.000 observations, and was adjusted until the design was stable and the prior parameters could be recuperated.