中国安全科学学报 ›› 2022, Vol. 32 ›› Issue (12): 141-149.doi: 10.16265/j.cnki.issn1003-3033.2022.12.0203

• 公共安全 • 上一篇    下一篇

基于客流加权的城市轨道交通网络抗毁性分析

马敏(), 胡大伟**(), 刘杰, 马壮林   

  1. 长安大学 运输工程学院,陕西 西安 710064
  • 收稿日期:2022-07-19 修回日期:2022-10-15 出版日期:2022-12-28
  • 通讯作者:
    ** 胡大伟(1963—),男,北京人,博士,教授,主要从事运输网络规划与设计、运输安全评估方面的研究。E-mail:
  • 作者简介:

    马 敏 (1974—),男,河南郑州人,博士研究生,高级政工师,主要研究方向为城市轨道交通规划和运营管理、网络复杂性与脆弱性等。E-mail:

  • 基金资助:
    陕西省自然科学基金资助(2021JZ-20); 长安大学中央高校基本科研业务专项资金资助(300102229304)

Invulnerability analysis of urban rail transit network based on weighted passenger flow

MA Min(), HU Dawei**(), LIU Jie, MA Zhuanglin   

  1. College of Transportation Engineering, Chang'an University, Xi'an Shaanxi 710064, China
  • Received:2022-07-19 Revised:2022-10-15 Published:2022-12-28

摘要:

为准确评估城市轨道交通车站失效对网络结构和服务质量的影响,首先,采用Space L方法,并考虑车站客流量,构建基于客流加权的城市轨道交通网络拓扑结构模型;然后,提出兼顾网络拓扑结构和服务质量的抗毁性综合评估指标,在度中心性、介数中心性和剩余容量3种负载分配策略下,分析随机攻击和蓄意攻击对城市轨道交通网络抗毁性的影响;最后,以2021年西安市轨道交通网络为例,验证模型的实用性和有效性。结果表明:客流量大或连接网络中心组团与分支的车站为城市轨道交通网络的关键车站;随着连续攻击次数的增加,强度最大的蓄意攻击对网络的破坏程度越来越大;在度数、介数和强度3种最大蓄意攻击策略下,网络抗毁性达到最优时,容量调节系数最小阈值为0.5,乘客换乘率的最大阈值为0.4。

关键词: 城市轨道交通网络, 抗毁性, 客流加权, 运输效能, 随机攻击, 蓄意攻击

Abstract:

In order to accurately assess the impact of urban rail transit station failure on network structure and service quality, a passenger flow weighted topological structure model of the urban rail transit network was constructed using both the Space L method and station passenger flow at first. Subsequently, a comprehensive evaluation index of invulnerability was proposed considering the network topology and service quality. The invulnerability of random and intentional attacks on urban rail transit networks was analyzed under three load distribution strategies:degree centrality distribution, betweenness centrality distribution, and residual capacity distribution. Finally, the Xi'an rail transit network in 2021 was taken as an example for verification and analysis. The results show that stations with larger passenger flow or connecting the central group and branch of the network are the key urban rail transit network stations. The damage degree on urban rail transit networks based on the maximum intensity of intentional attack is more serious than other attack strategies with increasing the number of continuous attacks. Under three intentional attacks, including the maximum degree, maximum betweenness, and maximum intensity, the minimum threshold of capacity adjustment coefficient and the maximum threshold of passenger transfer rate are 0.5 and 0.4, respectively, when the invulnerability performance of networks is optimal.

Key words: urban rail transit network, invulnerability, weighted passenger flow, transport efficiency, random attack, intentional attack