多元数据在北京轨道交通线网规划中的应用

随着城市轨道交通的发展,越来越多的难题显现出来,多元数据分析模型可为轨道交通线网规划提供定量技术手段。首先,介绍北京轨道交通多元数据库的构建,主要包括地铁AFC刷卡数据、手机信令数据、公交IC卡数据和浮动车数据等;其次,从地铁车站进出站客流特征、地铁车站换乘客流特征和线路断面客流特征三方面,阐述轨道交通现状客流特征;最后,以具体线路为例,对该线路的运营现状和线上重点车站存在的问题进行分析,并提出优化建议,展现多元数据在北京轨道交通线网规划中的应用。

Application of Big Data in Beijing Rail Transit Network Planning

With the development of urban rail transit, an increasing number of problems have emerged. The multivariate data analysis model provides quantitative technical means for rail transit network planning. This paper first introduces the construction of the multivariate Beijing rail transit database, predominantly comprising metro AFC data, mobile phone signaling data, IC card data on public transportation, and floating vehicle trajectory data. Second, this paper expounds on the current passenger flow characteristics of rail transit from three aspects: the passenger flow characteristics in and out of the station, the characteristics of transfer passenger flow, and the passenger flow characteristics along the section of line in question. Finally, taking a line as an example, this study analyzes the operation status of the line and the existing problems of the key station on the line – Xi’erqi Station. The paper proposes optimization suggestions, demonstrating the application of multivariate data in planning the Beijing rail transit network.