Key station identification of urban rail transit based on network redundancy

doi:10.16265/j.cnki.issn1003-3033.2022.12.0274

Abstract

Abstract:

In order to clarify the importance of different stations in urban rail transit network, a method of identifying key stations based on network redundancy was proposed. Topological redundancy and functional redundancy were defined from the perspectives of network topology and traffic functional characteristics. And taking Shanghai metro network as an example, key stations were identified. The research results show that the failure of a single important station identified based on network topological redundancy will cause 13.15% of the traffic tralvel(origin-destination, OD) in the network to be disconnected. After the failure of a single key station identified based on network functional redundancy, up to 10.1% of passengers in the network can not complete their travel through the rail transit network. For the ring-shaped radial rail transit network, the key stations identified based on network redundancy are mainly distributed in the branches radiated outward from the ring line and adjacent ring lines. In addition, the impact on rail transit network after multiple stations fail simultaneously depends not only on the importance of each station, but also on the spatial location distribution of each station in the rail transit network.

Key words: redundancy, urban rail transit, key stations, complex network, station failure

CUI Xin, LU Qingchang, LI Jianyu. Key station identification of urban rail transit based on network redundancy[J]. China Safety Science Journal, 2022, 32(12): 158-164.

Figures/Tables 10

Tab.1

Complex network characteristic indicators

指标		表达式	指标解释
度中心性		$D c (i) = ∑ j ≠ i ∈ N λ i j n - 1$	$λ i j$ 是用来判断节点i和j之间是否存在直接相邻边的变量,如果存在,那么 $λ i j = 1$ ,否则为0
介数中心性		$D b (i) = ∑ s ≠ t ∈ N σ s t (i) n (n - 1)$	$σ s t (i)$ 是用来判断节点对s与t的最短路径中是否通过节点i的变量,如果通过,该值为1,否则为0
紧密中心性		$D s (i) = n - 1 ∑ j ≠ i ∈ N d i j$	$d i j$ 为节点i与其他节点j之间的距离
指标	表达式			指标解释
网络效率	$E = 1 n (n - 1) ∑ i ≠ j ∈ G 1 d i j$			网络效率越高,则表示网络中节点之间的连通性越好
网络效率可达性	$E A = 1 f ∑ i ≠ j ∈ G f i j t i j$			$f i j$ 为从节点i出发到节点j的客流量; $t i j$ 为从节点i到节点j花费的时间; f为总乘客数

Tab.1

Fig.1

Fig.2

Tab.2

Tab.3

Fig.3

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Fig.5

Tab.4

Fig.6

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站点编号	站点名称	未连通的 OD/个	重要性评估值
34	东方体育中心	10 634	0.135
18	曹杨路	9 502	0.121
17	枫桥路	9 008	0.114
143	四平路	8 622	0.110
16	真如	8 510	0.108
63	镇坪路	8 510	0.108
118	宜山路	8 510	0.108
站点编号	站点名称	未连通的 OD/个	重要性评估值
15	上海西站	8 008	0.102
62	岚皋路	8 008	0.102
101	上海南站	8 008	0.102
260	桂林路	8 008	0.102
14	李子园	7 502	0.095
61	新村路	7 502	0.095
115	虹口足球场	7 502	0.095
135	锦江乐园	7 502	0.095

站点编号	站点名称	未满足需求乘客人数	关键性评估值
94	上海火车站	48 187	0.101
101	上海南站	43 647	0.092
118	宜山路	43 042	0.090
260	桂林路	39 605	0.083
93	中山北路	37 955	0.080
135	锦江乐园	37 787	0.079
259	漕河泾开发区	37 638	0.079
80	龙阳路	37 137	0.078
92	延长路	37 063	0.078
18	曹杨路	35 687	0.075
134	莲花路	34 709	0.073
91	上海马戏城	33 829	0.071
258	合川路	31 720	0.067
143	四平路	31 609	0.066
34	东方体育中心	31 329	0.066

序号	站点的编号	乘客数/万人
1	18、80、94、101、118	19.351 9
2	80、94、101、118、143	19.183 9
3	34、80、94、101、118	19.075 1
4	18、94、101、118、143	18.970 9
5	18、34、94、101、118	18.859 1
6	34、94、101、118、143	18.724 3
7	18、80、93、101、118	18.635 0
序号	站点的编号	乘客数/万人
8	18、80、92、101、118	18.598 7
9	18、80、94、101、260	18.570 5
10	18、80、94、101、259	18.474 5

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