“3060”双碳目标是我国关于碳排放有效治理的重大战略目标。城市轨道交通运营客流强度管理重点关注车站大客流形成机理、演变机制、预警概率、风险管理及应急处置。仅依靠工作人员人工巡查及通过对特定区域预设监控图像监测,无法实现主动预判客流预警。基于AFC大数据及智能视频图像识别处理分析原理,提出地铁突发大客流预警双维度耦合触发机制。构建突发大客流耦合触发判定矩阵,分级定义突发大客流预警风险概率,提出客流管控应对指南。以南京地铁突发大客流智能预警信息平台为例,验证了预警机理及耦合触发机制模型准确性及可操作性。
The carbon emission and carbon neutrality goal is China's solemn commitment to the effective management of carbon emissions by the international community. The passenger flow intensity management of urban rail transit operating enterprises focuses on the formation mechanism, evolution mechanism, early warning probability, risk management and emergency treatment of large passenger flow in stations. The active prediction of passenger flow can not be realized while Relying on the staff's manual inspection and through the preset monitoring image monitoring of a specific area. Based on AFC big data and intelligent video image recognition processing and analysis principle, a dual-dimension coupling trigger mechanism for subway sudden large passenger flow warning is proposed. The trigger judgment matrix of sudden large passenger flow coupling is constructed, and the early-warning risk probability of sudden large passenger flow is defined hierarchically. Then put forward the passenger flow control response guide. Taking Nanjing Metro intelligent early warning information platform for sudden large passenger flow as an example, the accuracy and operability of early warning mechanism and coupling trigger mechanism is verified.
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