基于云模型的城市轨道交通车站客流控制触发判别方法

Identification method for passenger inflow control in urban rail transit station based on cloud model

根据车站三级客流控制的特点分析了城市轨道交通车站设施设备的类别及乘客聚集程度判断指标,研究了城市轨道交通车站各主要设施设备客流状态级别的划分.然后,基于云模型的合成理论,构建了车站主要设施设备不同客流状态级别对应的模板云模型和实测设施设备客流状态合成指标云模型,通过计算两者之间的相似程度,提出了一种基于云模型的城市轨道交通车站客流控制触发判别方法.最后,以一级客流控制触发判别的关键观测点——站台为例,验证所提方法的有效性.结果表明,利用该方法能够准确地判别当前客流状态,有助于管理者根据客流状态及时采取相应的客流控制措施.

The station facility category of urban rail transit and the index of passenger aggregation degree were analyzed according to the features of three-level passenger flow control. The passenger inflow state levels of station facilities of urban rail transit were divided. Then, the template cloud model with different passenger inflow state levels and the synthetic index cloud model of the passenger inflow state measured by facilities were developed based on the synthesis theory of the cloud model. The identification method for passenger inflow control was proposed by calculating the similarity degree between the template cloud model and the synthetic index cloud model. Finally, the station, the key observation point of the first order passenger inflow control trigger discrimination, was taken as a case to verify the validity of the proposed method. The results show that the proposed method can accurately identify the current passenger inflow state, thus helping the manager timely take corresponding passenger inflow control measure according to the passenger inflow state.