“The overlooked majority”: Revealing the spatiotemporal travel patterns of low travel frequency passengers and their impact on metro systems

The “long-tail effect” observed in metro systems reflects that most passengers are Low Travel Frequency (LTF) users. However, research on the spatiotemporal travel patterns of this “overlooked majority” remains limited. These gaps predominantly arise from the focus on the “vital few”—high travel frequency passengers—who contribute larger and more regular passenger flow. This study is the first to conduct a horizontal (across different geographical locations) and vertical (across different years) comparative analysis on LTF passengers. It utilizes Automatic Fare Collection (AFC) datasets from Shanghai and Shenzhen metro stations across different years, combining statistical analysis, time-series decomposition, and spatial kernel density analysis to comprehensively reveal the travel characteristics and patterns of LTF passengers. The findings indicate that LTF passengers represent a broader segment of the metro passenger population and exhibit distinct and stable spatiotemporal characteristics across cities, years, and station types. Temporally, they significantly contribute to passenger flow during non-working days and off-peak periods, often appearing residual variability in time-series data. Spatially, they prefer destinations with shorter travel distances and stronger functional service attributes. Furthermore, public events like light shows strongly attract LTF passengers, offering new perspectives on metro passengers by highlighting the broader LTF passenger population. This research fills a critical gap in the study of LTF passengers and offers valuable insights into improving the efficiency and equity in service of metro operations and management.