Automatic fare collection (AFC) systems record both time and location information when a passenger enters or leaves the urban subway system. Using this data, this paper analyzed the travel time components including access time, platform wait time, transfer time, egress time, and in-vehicle time, as well as their corresponding distribution functions. Using this data, a time-dependent graphical model was created in order to estimate passenger time-space paths within an urban subway network. Based on subway train timetables, the time-extended network model produces feasible time-space paths. A time-space path sheds light on traveler movements throughout activity network. The proposed methodology provides a way to analyze subway passenger behavior, which can serve as a reference for dynamic traffic flow assignment for urban subway networks.
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