Modeling of Spatial Transit Mode Choice Based on Smart Card Data in Seoul

초록

In this study, using public transport smart card data observed in Seoul, Korea, we provide empirical evidence for the existence of a spatial correlation among transit mode choices at the Traffic Analysis Zone (TAZ) level. The Bayesian hierarchical modeling framework was applied to construct both spatial associations among TAZ levels and among commonly used utility functions with travel time and fare. We consider the binomial regression model with spatial effect by using a conditional autoregressive model (CAR) and regard a passenger’s choice of metro rather than bus transport as a reference category. The results show that the areas with a higher probability that passengers will choose a bus are clustered and that those regions have fewer metro stations than bus stations. We also found the spatial correlation is statistically meaningful and potentially useful in the modeling of a spatial transit mode choice. Consequently, a reliable spatial interaction would constitute valuable information for transportation agencies in terms of their route planning and scheduling based on the transit smart card data.