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How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds

机译:车站区域的建筑环境如何影响Metrorail的乘车率?使用梯度提升决策树来识别非线性阈值

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To inform the station-area planning, previous studies use direct ridership models to examine the relationship between the built environment around stations and transit ridership. Based on this framework, this study innovatively applies gradient boosting decision trees to investigate the non-linear effects of built environment variables on station boarding. Using the Metrorail data in the Washington metropolitan area, we found that station-area built environment characteristics collectively contribute to 34% of the predictive power for Metrorail ridership, after controlling for transit service factors and demographics. Built environment variables show threshold effects on Metrorail ridership. We further identified their effective ranges, guiding land use planning around stations. This study highlights the roles of compact and mixed land use development, the number of bus stops, and car ownership in determining the station-level ridership.
机译:为了向车站区域规划提供信息,以前的研究使用直接乘车率模型来检查车站周围的建筑环境与过境乘车率之间的关系。在此框架的基础上,本研究创新性地应用了梯度增强决策树,以研究建筑环境变量对车站登机的非线性影响。使用华盛顿都市区的Metrorail数据,我们发现,在控制过境服务因素和人口统计数据之后,车站区建成的环境特征总体上为Metrorail乘车率的预测能力贡献了34%。内置的环境变量显示了对Metrorail乘车率的阈值影响。我们进一步确定了它们的有效范围,指导车站周围的土地利用规划。这项研究强调了紧凑型和混合型土地利用开发,公交车站的数量以及汽车拥有量在确定车站一级乘车人数方面的作用。

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