Study on Invulnerability of Urban Rail Network Considering Sum of the Neighbors Degree

doi:10.16182/j.issn1004731x.joss.23-0612

Abstract

Abstract:

In order to solve the problem of network cascade paralysis caused by urban rail station or line failure, considering the influence of the first-order neighborhood of network nodes, the load distribution impedance coefficient is proposed based on the nonlinear capacity load model, and a nonlinear capacity load optimization model considering the sum of the neighbors degree is constructed. By optimizing load structure, the alternative probability of nodes during load redistribution is adjusted to reduce the number of node failures in the cascading process, thereby the rail network invulnerability is improved. Taking Chongqing rail network as an example, the rail network invulnerability under the two models was analyzed by simulation. The results show that the increase of load tolerance coefficient in the optimization model has a more significant effect on the improvement of network invulnerability. The larger the load distribution impedance coefficient of nodes in the optimization model, the lower the backup probability during load redistribution，the less likely to experience cascading overload.

Key words: rail network, nonlinear capacity load model, sum of the neighbor degree, load distribution impedance coefficient, invulnerability

CLC Number:

TP391.9

Li Shuqing, Song Yixiao, Zhong Guojian. Study on Invulnerability of Urban Rail Network Considering Sum of the Neighbors Degree[J]. Journal of System Simulation, 2024, 36(9): 2127-2136.

Figures/Tables 10

Fig. 1

Fig. 2

Fig. 3

Table 1

Critical stations of Chongqing rail network

站点编号	站点名称	$D c, i$
72	重庆北站南广场	0.026 3
12	沙坪坝	0.021 9
126	冉家坝	0.021 9
150	五里店	0.021 9
19	大坪	0.017 5
21	两路口	0.017 5
24	小什字	0.017 5
39	谢家湾	0.017 5
43	牛角沱	0.017 5
61	四公里	0.017 5
66	观音桥	0.017 5
67	红旗河沟	0.017 5
92	重庆北站北广场	0.017 5
93	保税港	0.017 5
120	重庆西站	0.017 5
149	红土地	0.017 5
153	上新街	0.017 5
186	上湾路	0.017 5

Table 1

Fig. 4

Fig. 5

Table 2

β=1.2、γ=1, θ and αc values of top 10 nodes in terms of network degree value

节点名称	$∑ n ∈ Γ i k n$	$k i$	$θ i$	$α c$
重庆北站南广场	15	6	2.5	0.349
沙坪坝	11	5	2.2	0.396
冉家坝	11	5	2.2	0.396
五里店	13	5	2.6	0.335
大坪	8	4	2.0	0.436
两路口	10	4	2.5	0.349
小什字	10	4	2.5	0.349
谢家湾	8	4	2.0	0.436
牛角沱	10	4	2.5	0.349
四公里	8	4	2.0	0.436

Table 2

Fig. 6

Fig. 7

Fig. 8

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