Resilience assessment method of urban rail transit system under cascading failure

doi:10.16265/j.cnki.issn1003-3033.2024.09.1963

Abstract

Abstract:

In order to identify high-risk stations in urban rail transit systems and improve network resilience and operational safety, a performance function model was constructed to evaluate the network resilience by selecting network efficiency, average shortest path length and maximum connection sub-graph as indicators, and an evaluation method for critical stations was proposed, considering topological structure and passenger flow distribution equilibrium. Taking Nanjing Metro as an example, three cascading failure modes, descending critical degree, descending betweenness centrality and random sequence, are adopted. The characteristics of resilience degradation under different cascading failures are simulated respectively in the unweighted network and the weighted network. The results show that the critical stations are similar on weekdays and weekends. The resilience performance decreases most rapidly in the early stages of failures in descending order of critical stations. Compared with topology networks, the resilience index of passenger flow-weighted networks decreases faster in the early stages of cascading failures. Strengthening the control of critical stations when cascading failures do not spread widely can help reduce the loss of network resilience.

Key words: urban rail transit, network resilience, cascading failure, critical stations, weighted network

CLC Number:

CHEN Jinyi, LI Tiezhu, GUO Jingwen, LIU Hui, CHEN Haibo. Resilience assessment method of urban rail transit system under cascading failure[J]. China Safety Science Journal, 2024, 34(9): 202-208.

Figures/Tables 6

Table 1

Table 2

Fig.1

Fig.2

Fig.3

Table 3

References 17

[1]	交通运输部. 2023年城市轨道交通运营数据速报[EB/OL].(2024-01-12). https://mp.weixin.qq.com/s?__biz=MzI3MDQwMDQ5NQ==&mid=2247593667&idx=1&sn=5a5fd0f406b50ad9307620d7e3964d35&scene=0.
[2]	鞠艳妮, 李宗平, 陈宇帆, 等. 区域轨道交通系统节点重要度及故障恢复研究[J]. 中国安全科学学报, 2021, 31(2):112-119. doi: 10.16265/j.cnki.issn 1003-3033.2021.02.016
	JU Yanni, LI Zongping, CHEN Yufan, et al. Study on node importance and failure recovery of regional rail transit system[J]. China Safety Science Journal, 2021, 31(2):112-119. doi: 10.16265/j.cnki.issn 1003-3033.2021.02.016
[3]	马敏, 胡大伟, 舒兰, 等. 城市轨道交通网络韧性评估及恢复策略[J]. 吉林大学学报:工学版, 2023, 53(2):396-404.
	MA Min, HU Dawei, SHU Lan, et al. Resilience assessment and recovery strategy on urban rail transit network[J]. Journal of Jilin University: Engineering and Technology Edition, 2023, 53(2):396-404.
[4]	ZHANG Jiefei, REN Gang, SONG Jianhua. Resilience-based restoration sequence optimization for metro networks: a case study in China[J]. Journal of Advanced Transportation, 2022: DOI: 10.1155/2022/8595356.
[5]	张雯婕, 胡军红, 闻成维, 等. 考虑网络韧性的城市轨道交通故障恢复研究[J]. 中国安全科学学报, 2023, 33(4):179-186. doi: 10.16265/j.cnki.issn1003-3033.2023.04.1770
	ZHANG Wenjie, HU Junhong, WEN Chengwei, et al. Research on urban rail failure recovery considering network resilience[J]. China Safety Science Journal, 2023, 33(4):179-186. doi: 10.16265/j.cnki.issn1003-3033.2023.04.1770
[6]	陈峰, 胡映月, 李小红, 等. 城市轨道交通有权网络相继故障可靠性研究[J]. 交通运输系统工程与信息, 2016, 16(2):139-145.
	CHEN Feng, HU Yingyue, LI Xiaohong, et al. Cascading failures in weighted network of urban rail transit[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(2):139-145.
[7]	MA Fei, LIANG Yuan, YUEN K F, et al. Assessing the vulnerability of urban rail transit network under heavy air pollution: a dynamic vehicle restriction perspective[J]. Sustainable Cities and Society, 2020:DOI:10.1016/j.scs.2019.101851.
[8]	熊志华, 姚智胜. 轨道交通网络级联失效影响范围研究[J]. 交通运输系统工程与信息, 2020, 20(1):12-18.
	XIONG Zhihua, YAO Zhisheng. Influence scope of cascading failure on rail transit system[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(1):12-18.
[9]	LU Qingchang, ZHANG Lei, XU Pengcheng, et al. Modeling network vulnerability of urban rail transit under cascading failures: a coupled map lattices approach[J]. Reliability Engineering & System Safety, 2022: DOI:10.1016/j.ress.2022.108320.
[10]	LU Qingchang. Modeling network resilience of rail transit under operational incidents[J]. Transportation Research Part A: Policy and Practice, 2018, 117:227-237.
[11]	胡映月, 陈峰, 陈培文, 等. 基于网络客流传播的轨道交通关键站点识别[J]. 西南交通大学学报, 2017, 52(6):1193-1200,1215.
	HU Yingyue, CHEN Feng, CHEN Peiwen, et al. Critical station identification based on passenger propagation in urban mass transit network[J]. Journal of Southwest Jiaotong University, 2017, 52(6): 1193-1200,1 215.
[12]	BRUNEAU M, CHANG S E, EGUCHI R T, et al. A framework to quantitatively assess and enhance the seismic resilience of communities[J]. Earthquake Spectra, 2003, 19(4): 733-752.
[13]	雷勋平, 邱广华. 基于熵权TOPSIS模型的区域资源环境承载力评价实证研究[J]. 环境科学学报, 2016, 36(1):314-323.
	LEI Xunping, QIU Guanghua. Empirical study about the carrying capacity evaluation of regional resources and environment based on entropy-weight TOPSIS model[J]. Acta Scientiae Circumstantiae, 2016, 36(1):314-323.
[14]	BRIN S, PAGE L. The anatomy of a large-scale hypertextual Web search engine[J]. Computer Networks and ISDN Systems, 1998, 30: 107-117.
[15]	来逢波, 许冰, 续颖, 等. 高铁复杂网络拓扑特征及节点中心性研究[J]. 山东大学学报:工学版, 2022, 52(6):14-22.
	LAI Fengbo, XU Bing, XU Ying, et al. Study on topological characteristics and node centrality of high-speed railway complex network[J]. Journal of Shandong University :Engineering Science, 2022, 52 (6): 14-22.
[16]	黄志远, 徐瑞华, 杨儒冬, 等. 城市轨道交通客流网络分布均衡性评价[J]. 交通运输系统工程与信息, 2018, 18(3):139-145.
	HUANG Zhiyuan, XU Ruihua, YANG Rudong, et al. Evaluation on equilibrium of passenger flow distribution on urban rail transit network[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(3):139-145.
[17]	LEE K, JUNG W S, PARK J S, et al. Statistical analysis of the metropolitan Seoul subway system: network structure and passenger flows[J]. Physica A-Statistical Mechanics and Its Applications, 2008, 387(24): 6 231-6 234.

时段		基尼系数
周一上行	(7:30-8:00]	0.606
	(8:00-8:30]	0.594
	(8:30-9:00]	0.582
周一下行	(7:30-8:00]	0.488
	(8:00-8:30]	0.531
	(8:30-9:00]	0.554
周六上行	(7:30-8:00]	0.560
	(8:00-8:30]	0.564
	(8:30-9:00]	0.552
周六下行	(7:30-8:00]	0.481
	(8:00-8:30]	0.491
	(8:30-9:00]	0.517

关键程度排序	周一		周六
关键程度排序	站点名称	关键程度	站点名称	关键程度
1	南京南站	0.907	南京南站	0.947
2	新街口	0.632	新街口	0.601
3	大行宫	0.608	大行宫	0.592
4	南京站	0.522	南京站	0.505
5	鸡鸣寺	0.420	鸡鸣寺	0.437
6	安德门	0.287	安德门	0.260
7	柳洲东路	0.087	柳洲东路	0.058
8	天润城	0.066	新庄	0.048
9	新庄	0.066	小市	0.044
10	小市	0.066	天润城	0.043
11	五塘广场	0.063	五塘广场	0.042
12	三山街	0.059	三山街	0.042
13	上元门	0.058	中华门	0.039
14	中华门	0.058	上元门	0.039
15	张府园	0.057	张府园	0.038
16	浮桥	0.050	浮桥	0.034
17	天隆寺	0.019	珠江路	0.024
18	双龙大道	0.017	天隆寺	0.014
19	软件大道	0.009	双龙大道	0.013
20	花神庙	7×10^-5	软件大道	0.005
21	—	—	花神庙	7×10^-5

时间步	无权网络			加权网络
时间步	随机	关键程度	BC	随机	关键程度	BC
1	0.994	0.846	0.859	0.995	0.830	0.838
2	0.984	0.677	0.781	0.978	0.654	0.724
3	0.974	0.553	0.718	0.962	0.520	0.636
4	0.942	0.461	0.628	0.941	0.428	0.550
5	0.893	0.384	0.540	0.909	0.360	0.476
6	0.815	0.326	0.473	0.834	0.310	0.419
7	0.728	0.281	0.422	0.742	0.272	0.375
8	0.663	0.246	0.383	0.670	0.242	0.342
9	0.603	0.219	0.353	0.610	0.219	0.316
10	0.548	0.198	0.323	0.557	0.201	0.291
11	0.503	0.180	0.295	0.514	0.185	0.268
12	0.465	0.165	0.271	0.477	0.173	0.249
13	0.433	0.153	0.250	0.446	0.162	0.232
14	0.406	0.142	0.233	0.419	0.152	0.218
15	0.382	0.133	0.217	0.395	0.144	0.205
16	0.361	0.125	0.204	0.374	0.137	0.194
17	0.342	0.117	0.192	0.355	0.131	0.185
18	0.325	0.111	0.182	0.337	0.125	0.176
19	0.309	0.105	0.172	0.320	0.120	0.168
20	0.294	0.100	0.164	0.304	0.115	0.161