摘要
为了更好防范风险,以角门西站为例,选取平时和临近春节的工作日数据,从拥挤风险时段和局部空间拥挤风险两方面分析研究地铁站客流拥挤风险.根据AFC数据,分析乘客在不同工作日进出站和换乘客流特征,确定客流拥挤风险时段;通过Anylogic仿真,用热力图识别地铁站客流拥挤位置.基于服务水平等级标准,提出了1种用密度、单位宽度行人流量和速度参数判别地铁站不同位置的拥挤状态的方法.分析了平时和临近春节的工作日早高峰的客流变化情况,并且用拥挤持续时间来衡量客流拥挤风险的大小.结果表明:该方法可为地铁运营方应对拥挤风险提供理论支撑.
In order to minimize risks,taking Jiaomenxi Station as an example,this research selects the data of weekdays in ordinary times and near the Spring Festival to analyze and study the crowding risk of subway stations from two aspects:congestion risk period and local space crowding risk.According to the AFC data,the characteristics of inbound,outbound and transfer passenger flow in different working days are analyzed,and crowded passenger flow periods are determined.Through Anylogic simulation,the heat map is used to identify crowded locations in the metro station.Based on the level of service standard,a method to distinguish the congestion status of different positions by density,pedestrian flow per unit width and speed parameters is determined.This study analyzes the changes of the flow in the morning peak on weekdays and around the Spring Festival,and uses the duration of crowding to measure the risk of passenger flow congestion.The results show that it can provide theoretical support for subway operators to deal with the risk of congestion.
作者
孙梦凡
周慧娟
SUN Mengfan;ZHOU Huijuan(Beijing Key Laboratory of Intelligent Control Technology for Urban Road Traffic,North China University of Technology,Beijing 100144,China)
出处
《交通工程》
2023年第2期92-99,共8页
Journal of Transportation Engineering
关键词
出行规律
服务水平
风险分析
客流仿真
travel characteristics
the level of service
risk analysis
passenger flow simulation
