Chapters authored
Validating Activity-Based Travel Demand Models Using Mobile Phone Data
Activity-based travel demand models predict travel sequences on a day for each individual in a study region. These sequences serve as important input for travel demand estimate and forecast in the area. However, a reliable method to evaluate the generated sequences has been lacking, hampering further development and application of the models. In this chapter, we use travel behavioral information inferred from mobile phone data for such validation purposes. Our method is composed of three major steps. First, locations where a user made calls on a day are extracted from his/her mobile phone records, and these locations form a location trajectory. All the trajectories from the user across multiple days are then transformed into actual travel sequences. The sequences derived from all phone users are further classified into typical patterns which, along with their relative frequencies, define travel profiles. These profiles characterize current travel behavior in the study region and can thus be utilized for assessing sequences generated from activity-based models. By comparing the obtained profiles with statistics drawn from conventional travel surveys, the validation potential of the proposed method is demonstrated.
Part of the book: Mobile Computing