[关键词]
[摘要]
为解决换乘车站分类标准缺失或不精准的问题,本文从用地、区位、客流三个维度分析换乘站分类的影响因素并提出分类指标计算方法,结合K-Means聚类算法构建了基于多因素聚类的换乘站分类方法,应用南京地铁换乘站开展实例分析。结果表明:与单因素(仅用地、仅区位、仅客流)聚类方法相比,多因素聚类方法在分类均匀度、聚类间距、实际分类效果等方面具有明显优势。结合分类结果,提出南京地铁换乘站宜按综合枢纽型、公共中心型、居住生活型、产业办公型及外围接驳型五类划分,并分析了换乘站在不同要素上的阈值特性及取值建议。本文研究成果可为未来地铁换乘站规划及设计提供重要借鉴意义。
[Key word]
[Abstract]
In order to solve the problem of the lack or inaccuracy of the transfer station classification standard, this paper analyzes the influencing factors of the transfer station classification from three dimensions of land use, location, and passenger flow, and proposes a calculation method for classification indicators. Combined with the K-Means clustering algorithm, a multi-factor classification method of transfer station is constructed. and the transfer station of Nanjing Metro was applied to carry out case analysis. The results show that:compared with the single factor (land only, location only, and passenger flow only) clustering method, the multi-factor clustering method has obvious advantages in classification uniformity, clustering distance, and actual classification effect. Combining the classification results, it is proposed that the transfer stations of Nanjing Metro should be classified into five categories: integrated hub type, public center type, residential and life type, industrial office type and peripheral connection type, and analyzed the threshold characteristics and value recommendations of the different elements of the transfer station. The research results of this paper can provide important reference for subway transfer station planning and design in the future.
[中图分类号]
[基金项目]
国家科技攻关计划