Hub Node Identification in Urban Rail Transit Network Evolution Using a Ridership-Weighted Network

Tian Tian, Yanqiu Cheng, Yichen Liang, Chen Ma, Kuanmin Chen, Xianbiao Hu
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Abstract

With the development of the urban rail transit network (URTN), the network structure and performance have changed, and the node importance has also been redistributed. However, little research has been done on how hub nodes change as the network develops over a lengthy period. Moreover, most hub node identification methods only focus on the analysis of topological networks or single-dimension measurements, resulting in inaccurate identification results. To overcome the above limitations, a novel method of hub node identification is proposed. Based on the ridership-weighted network model, the node centrality and reliability are aggregated to quantify the weighted comprehensive importance of the nodes. Furthermore, network invulnerability measurement is used to demonstrate the effectiveness of the proposed method. This method is applied to the Xi’an Urban Rail Transit Network (XURTN) from 2011 to 2021. With the XURTN’s development, its connectivity, balance, and fault tolerance have improved. After the basic network skeleton was formed, the number and proportion of hub nodes increased steadily. By comparing the spatial characteristics of the identified hub nodes over two successive periods, it can be found that the evolution direction of the hub nodes is correlated with the type of new lines and coincides also with the development direction of the urban area. In addition, the node orders of the proposed method have a greater impact on the network vulnerability, in which the network-weighted efficiency [Formula: see text] decreases faster and more dramatically, that is, 1.17%–45.75% more than that of other methods. Overall, this study provides a basis for the URTN and station planning and management.
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利用乘客加权网络识别城市轨道交通网络演进中的枢纽节点
随着城市轨道交通网络(URTN)的发展,网络结构和性能发生了变化,节点的重要性也重新分配。然而,关于枢纽节点如何随着网络的长期发展而发生变化的研究却很少。此外,大多数枢纽节点识别方法只关注拓扑网络分析或单一维度测量,导致识别结果不准确。为了克服上述局限性,本文提出了一种新颖的枢纽节点识别方法。基于乘客加权网络模型,将节点中心性和可靠性进行汇总,量化节点的加权综合重要性。此外,还利用网络脆弱性测量来证明所提方法的有效性。该方法适用于 2011 年至 2021 年的西安城市轨道交通网(XURTN)。随着西安城市轨道交通网的发展,其连通性、平衡性和容错性都得到了提高。网络基本骨架形成后,枢纽节点的数量和比例稳步增长。通过比较已识别的枢纽节点在两个连续时期的空间特征,可以发现枢纽节点的演化方向与新线类型相关,也与城市区域的发展方向相吻合。此外,所提方法的节点阶数对网络脆弱性的影响较大,其中网络加权效率[公式:见正文]下降更快、更明显,即比其他方法多 1.17%-45.75%。总之,本研究为 URTN 和车站规划与管理提供了依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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