| Summary: | Objective Urban rail transit stations are facing the challenges of increasing passenger flow pressure and insufficient intelligent means. To improve the efficiency and intelligent level of passenger flow organization in station, it is necessary to adopt more advanced informational method and means. Method The development and characteristics of temporal knowledge graph (TKG) are described. By introducing the temporal information of the station passenger flow, a passenger flow organization model based on TKG is established. The model is applied to a station passenger flow organization on Beijing Metro Line 2, and the TKG model for this station is established. A graphical display is performed using ArangoDB database software to study the dynamic evolution process of the station passenger flow organization. Result & Conclusion The model can provide informational means and technical support for the advanced prediction, rapid response, effective implementation and intelligent early warning in the station passenger flow organization.
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