Relational analysis of route searches and transportation IC card use

Route search data are saved in public transportation route search systems. These data record the potential travel plans of searchers and are expected to serve as a reliable source of information to predict travel demand. However, route search data merely represent latent demand and their relationship with actual traffic demand is not known. The purpose of this study was to identify the relationship between the number of route searches and the number of actual public transportation users to predict traffic demand using route search data. To achieve this, both route search data and transportation IC card data were analyzed for the Kotoden lines that operate in Kagawa Prefecture, Japan. By adopting an approach that combined bivariate state-space and weighted regression models, we extracted the varying hidden relationships between the two seemingly unrelated data types and modeled the behaviorally related parts. The results revealed a positive correlation between sudden surges in the number of route searches and transportation IC card use.