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Exploring urban rail transit station-level ridership growth with network expansion

机译:通过网络扩展探索城市轨道交通车站一级的乘客量增长

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Urban rail transit (URT) is experiencing rapid network expansion in metropolises in China. The network expansion not only improves accessibility, but also motivates the surrounding land use development, which may have important effects on the ridership of existing stations. Considering the network scale, station-level accessibility increment, station characteristics, etc., this study develops an approach to explore the URT station-level ridership growth with network expansion, which can provide transit resource allocation guidance for URT agencies. Instead of collecting land use and socioeconomic data with huge labor and cost, we make good use of Automatic Fare Collection (AFC) data to develop proxy variables. Based on the temporal distribution of station-level ridership, a proxy for land use type is proposed. Then, multiple explanatory variables representing network expansion are introduced, and further the multivariate regression models are established to explore station-level ridership growth with network topology change and surrounding land use development. The results show that the proposed approach has good abilities to explain station-level ridership growth with network expansion and can make a response to network topology change and surrounding land use change.
机译:城市轨道交通(URT)在中国的大都市中正在经历快速的网络扩展。网络的扩展不仅改善了可访问性,而且还刺激了周边土地利用的发展,这可能对现有车站的载客量产生重要影响。考虑到网络规模,站点级可访问性增量,站点特性等,本研究开发了一种探索随着网络扩展而增加URT站点级客流量的方法,可以为URT机构提供过境资源分配指导。我们没有使用大量的劳动力和成本来收集土地使用和社会经济数据,而是充分利用了自动票价收集(AFC)数据来开发代理变量。基于站级乘车人的时间分布,提出了一种土地利用类型的代理。然后,引入了代表网络扩展的多个解释变量,并进一步建立了多元回归模型,以探索随着网络拓扑变化和周围土地利用发展而产生的站级客流量的增长。结果表明,所提出的方法具有很好的解释随着网络扩展站级客流量增长的能力,并且可以对网络拓扑结构变化和周围土地利用变化做出响应。

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