  The results of transportation infrastructure network analyses have been used
to analyze complex networks in a topological context. However, most modeling
approaches, including those based on complex network theory, do not fully
account for real-life traffic patterns and may provide an incomplete view of
network functions. This study utilizes trip data obtained from the Beijing
Subway System to characterize individual passenger movement patterns. A
directed weighted passenger flow network was constructed from the subway
infrastructure network topology by incorporating trip data. The passenger flow
networks exhibit several properties that can be characterized by power-law
distributions based on flow size, and log-logistic distributions based on the
fraction of boarding and departing passengers. The study also characterizes the
temporal patterns of in-transit and waiting passengers and provides a
hierarchical clustering structure for passenger flows. This hierarchical flow
organization varies in the spatial domain. Ten cluster groups were identified,
indicating a hierarchical urban polycentric structure composed of large
concentrated flows at urban activity centers. These empirical findings provide
insights regarding urban human mobility patterns within a large subway network.
