Exploring the difference between ridership patterns of subway and taxi: Case study in Seoul

Abstract

Understanding urban mobility patterns and their connections with different area characteristics is a traditional topic in urban studies, considering its importance for the planning and management of urban facilities, transportation systems, and services. Data recordings about trips using different means of transportation, such as a subway, bus, and taxi have been collected because of the development of IT technologies; such development has motivated various research related to uncovering detailed urban mobility patterns and factors that affect mobility. However, many works usually focus only on a specific means of transportation and fail to present different aspects of ridership patterns for other means of transportation. In this study, subway and taxi data were analyzed simultaneously to uncover factors on human mobility depending on the means of transportation in Seoul. The present research focused on regions nearby subway stations. Data mining techniques, such as clustering and classification, were employed. Different distinct ridership patterns of subway and taxi were detected using clustering; moreover, the difference between ridership patterns and spatial distributions of clusters were examined. A two-step classification analysis was then performed to determine factors that influence ridership patterns.