  The subway as the most important transportation for daily urban commuting is
a typical non-equilibrium complex system, composed of 2 types of basic units
with service relationship. One challenge to operate it is passengers be
stranded at stations, which arise from the spatiotemporal mismatch of supply
scale and demand scale. More seriously, there is a special phenomenon of the
propagation of passenger stranding (PPS) by forming stranded stations clusters,
which significantly reduces the service efficiency. In this study, Beijing
subway as an example is studied to reveal the nature of PPS phenomena from a
view point of statistical physics. The simulation results demonstrate
phase-transition-like behaviors depending on the ratio of service supply scale
and demand scale. The transition point can quantitatively characterize the
resilience failure threshold of service. The eigen microstate method is used to
extracting the fundamental patterns of PPS phenomena. Moreover, this study
offers a theoretical foundation for strategies to improve service, such as
topological planning and train timetable optimization. The methodology
developed in present work has significant implications for study of other
service systems.
