摘要
结合国内外对限流阈值的研究,以站台滞留人数达到阈值为限流启动条件,构建地铁站点限流预警模型。以北京地铁十号线某站为例,验证了小波神经网络在短时客流预测方面的有效性,且进行了限流方案的详细分析。结果表明,该模型可得到限流时间和限流流率,以及站外最大排队长度等量化指标,为实现动态限流预警提供了科学依据。
According to the researches on rational threshold of passenger flow at subway station in the world,a flow limitation early warning model is established on the premise that the accumulated number of station passengers is below the preset threshold in the time horizon.Then,a station of Beijing subway Line 10 is presented to verify the effectiveness of WNN in short-term passenger flow forecasting,and the flow limitation strategy is analyzed in detail.The result shows that this model could obtain the quantitative indicators including the limitation time,limitation rate and the maximum queue length outside the station,providing a scientific basis for the dynamic early warning of passenger flow at metro stations.
作者
杨安安
陈艳艳
黄建玲
熊杰
王少华
YANG An-an;CHEN Yanyan;HUANG Jianling;XIONG Jie;WANG Shaohua(Beijing Key Laboratory of Traffic Engineering,Beijing University of Technology,100124,Beijing,China)
出处
《城市轨道交通研究》
北大核心
2018年第10期29-33,共5页
Urban Mass Transit
关键词
地铁
限流
预警模型
小波神经网络
短时客流预测
subway
flow limitation
early warning model
wavelet neural network(WNN)
short-term passenger flow forecasting
