Aggregated Metro Trip Patterns in Urban Areas of Hong Kong: Evidence from Automatic Fare Collection Records

Abstract

The automatic fare collection (AFC) system incorporating smart card technology is widely used in transportation systems for revenue management, but the data from this could be mined for wide-ranging applications. This paper used AFC data of eight metro stations in the central area of Hong Kong to analyze metro trip patterns at an aggregate level. Based on the ridership differences between days, time periods, and directed flows, empirical data were categorized into three groups to better understand the station area characteristics. Compared to previous studies, it was found that factors may play varied roles in determining trip quantities for divergent station areas. Shopping and recreational factors demonstrated a statistically significant relationship with metro trips during the afternoon peak at exit flow and the evening peak at entry flow in the commercial districts of Hong Kong, such as Causeway Bay, Tsim Sha Tsui, and Mong Kok. This suggests that the distinctive context characteristics of the study area should be taken into consideration when selecting major determinants for transit trip patterns. The results of this study may provide promising insights for mass transit planning and the understanding of transit behavior in central urban areas.