Real-time Evaluation Model for Metro Station Passenger Flow Streamline Congestion State - SHI Pingcui; HU Hua; HAO Yanxi; FANG Yong; LIU Zhigang (Chengshi guidao jiaotong yanjiu, 2025)
[Objective] Implementing precise initiation, performance evaluation and dynamic information dissemination of metro station large passenger flow management and control measures requires more effective support. It is necessary to consider the diversity of facility types and the concurrency of congestion from the perspective of passenger flow streamlines. A congestion state real-time evaluation model of metro station passenger flow streamline for assessing real-time passenger flow conditions is established. [Method] Passenger flow streamline facilities are categorized into node facilities and passageway facilities. Based on the spatiotemporal propagation characteristics of streamline congestion and the feasibility of extracting passenger flow parameters via video recognition technology, three evaluation indicators―average delay time at all node facilities, queue space overflow rate at all node facilities, and variation coefficient in walking speed across all passageway facilities―are defined and formulated. Targeting dynamic information dissemination, the instantaneous congestion level classification criteria for a given station streamline is determined based on ant colony clustering algorithm, and the CRITIC method (an objective weighting approach) is used to determine the weights of streamline instantaneous congestion indicators. Taking the east station-hall main inbound passenger flow streamline of Shanghai Rail Transit Caohejing Hi-Tech Park Station as a case study, the streamline′s instantaneous congestion levels are analyzed, as well as the changes in streamline overall congestion levels under different congestion information dissemination intervals. [Result & Conclusion] The congestion state of passenger flow streamline is related to that of multiple individual node facilities. By conducting a comprehensive analysis, this model provides a more holistic basis for determining the initiation timing, sequencing, and effectiveness of large passenger flow management and control measures across diffe-rent levels of nodes and streamlines.