Validation of activity-based travel demand model using smart-card data in Seoul, South Korea

Abstract

This study aims to validate an activity-based travel demand model, FEATHERS, using smart-card data which is collected in Seoul, South Korea, and to discuss some limits and challenges in the prediction of public traffic demands. To achieve the goal, global/local trip pattern indices and a hot-spot analysis were applied for the validation test as a comparison method in this study. Using those methods, the public traffic demands predicted by the simulation in the study area were evaluated comparing with ones in the smart-card data. As a result, FEATHERS Seoul shows the enough performance in predicting the global pattern of the public traffic demands, but a low performance in a local pattern, particularly in some areas with a mixture land-use type and/or a frequent public transit. This is because the current model does not handle such a complicate type of land-use and also a multimodal trip in the simulation process. In conclusion, this study addressed the limits of the current model through the validation test using smart-card data and suggested some solution to the improvement in the specific models As a future work, we will apply smart-card data for the validation of the models operated in FS, such as a location choice model and a trip mode choice model.