动态网络模型的地铁网络关键节点识别OA
Dynamic network modeling for key node identification in subway networks
城市交通网络的动态特性分析对优化运营效率至关重要.针对目前地铁网络构建与分析仍处于静态化的问题,本文基于线路空间(Space-L)模型,构建列车始发-目的地服务时空网络(OD-TS),通过引入时间维度的旅行弧与换乘弧,描述地铁网络的动态特征.结合南昌市地铁与公交数据,采用K壳分解法(K-Shell)量化分析站点在不同时段的关键性.结果表明,永叔路站、阳明公园站、地铁大厦站等站点在高峰期的K-Shell值显著偏高;部分站点的关键性在工作日与非工作日存在明显差异,体现网络的结构异质性与功能多样性.本文方法可为交通资源优化配置与多模态系统建模提供理论支撑与决策建议.
The analysis of the dynamic characteristics of the urban transportation network is crucial to optimizing operational effi-ciency.Aiming at the static problems of subway network construction and analysis,this paper constructed a time-space train origin-destination service network(OD-TS)based on the Space-L model and introduced the travel arc and transfer arc in the time dimension to describe the dynamic characteristics of the subway network.By combining the subway and bus data in Nanchang City,the criticality of stations in different time periods was quantitatively analyzed using K-shell decomposition(K-Shell).The results show that Yongshu Road Station,Yangming Park Station,and Metro Building Station have significantly higher K-Shell values during peak hours,and some stations have obvious differences between weekdays and non-workdays,reflecting the structural heterogeneity and functional diversity of the network.This paper provides theoretical support for optimal allocation of transportation resources and multi-modal system modeling.
覃渊渊;吴静;徐诗奕
东华理工大学 测绘与空间信息工程学院,江西 南昌 330013东华理工大学 测绘与空间信息工程学院,江西 南昌 330013||东华理工大学 江西省流域生态过程与信息重点实验室,江西 南昌 330013||东华理工大学 自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室,江西 南昌 330013东华理工大学 测绘与空间信息工程学院,江西 南昌 330013
天文与地球科学
城市交通关键节点地铁网络复杂网络
urban transportationkey nodesubway networkcomplex network
《北京测绘》 2026 (2)
137-141,5
国家自然科学基金(41601416)
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