Strategies to Enhance the Resilience of an Urban Rail Transit Network

被引:37
|
作者
Chen, Jinqu [1 ]
Liu, Jie [1 ,2 ]
Peng, Qiyuan [1 ,3 ,4 ]
Yin, Yong [1 ,3 ,4 ]
机构
[1] Southwest Jiaotong Univ, Sch Transportat & Logist, Chengdu, Sichuan, Peoples R China
[2] Kunming Univ Sci & Technol, Fac Transportat Engn, Kunming, Yunnan, Peoples R China
[3] Southwest Jiaotong Univ, Natl United Engn Lab Integrated & Intelligent Tra, Chengdu, Sichuan, Peoples R China
[4] Southwest Jiaotong Univ, Natl Engn Lab Integrated Transportat Big Data App, Chengdu, Sichuan, Peoples R China
基金
国家重点研发计划;
关键词
public transportation; rail transit systems; rail; railroad infrastructure design and maintenance; resilience and sustainability; METRICS;
D O I
10.1177/03611981211037888
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
An urban rail transit (URT) system is an important component of an urban infrastructure system; however, it is vulnerable to disturbances, such as natural disasters and terrorist attacks. Constructing a highly resilient URT network has practical significance for enhancing its capability to respond to disturbances. In this paper, models are developed to optimize a URT network's structure with regard to resilience and to enhance the resilience of a disrupted URT network. A bi-level programming model that aims to maximize a URT network's global accessibility and global efficiency is formulated to optimize the structure of the network. A novel repair strategy, called the simulation repair strategy, is proposed to enhance the resilience of a disrupted URT network by optimizing the repair sequence of failed stations. The models are utilized to enhance the resilience of the Chengdu subway network. The result indicates that the bi-level programming model guides the construction of new links to optimize the structure of the Chengdu subway network. Deliberate attacks are more harmful to the Chengdu subway network than random attacks. The network's operators need to pay attention to the operations of critical stations (e.g., Chunxi Road station and Tianfu Square station) to prevent disturbances from exerting considerable negative effects on the network's normal operations. The simulation repair strategy exhibits higher repair efficiency than the conventional repair strategy, and it effectively enhances the resilience of the disrupted Chengdu subway network.
引用
收藏
页码:342 / 354
页数:13
相关论文
共 50 条
  • [1] Recovery Strategies for Urban Rail Transit Network Based on Comprehensive Resilience
    Zheng, Mingming
    Zuo, Hanzhang
    Zhou, Zitong
    Bai, Yuhan
    SUSTAINABILITY, 2023, 15 (20)
  • [2] Resilience assessment and recovery strategy on urban rail transit network
    Ma M.
    Hu D.-W.
    Shu L.
    Ma Z.-L.
    Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2023, 53 (02): : 396 - 404
  • [3] A Review of Resilience Assessment and Recovery Strategies of Urban Rail Transit Networks
    Hu, Junhong
    Yang, Mingshu
    Zhen, Yunzhu
    SUSTAINABILITY, 2024, 16 (15)
  • [4] Resilience assessment of an urban rail transit network under natural disasters
    Chen, Jinqu
    Liu, Xiaowei
    Hu, Xinyue
    Du, Bo
    Yin, Yong
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2025, 139
  • [5] Resilience Enhancement of an Urban Rail Transit Network by Temporarily Adjusting Regular Bus Transit Operation
    Chen, Jinqu
    Yue, Mengfan
    Du, Bo
    Peng, Qiyuan
    Yin, Yong
    2023 IEEE 26TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, ITSC, 2023, : 277 - 282
  • [6] Resilience assessment of an urban rail transit network: A case study of Chengdu subway
    Chen, Jinqu
    Liu, Jie
    Peng, Qiyuan
    Yin, Yong
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2022, 586
  • [7] Resilience Analysis of Urban Rail Transit Network Under Large Passenger Flow
    Wang, Ning
    2022 IEEE 22ND INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY, AND SECURITY COMPANION, QRS-C, 2022, : 444 - 446
  • [8] Controllability of Urban Rail Transit Network
    Zeng, Lu
    Qin, Yong
    Liu, Jun
    Wang, Li
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES FOR RAIL TRANSPORTATION (EITRT) 2017: TRANSPORTATION, 2018, 483 : 873 - 883
  • [9] A scenario model for enhancing the resilience of an urban rail transit network by adding new links
    Yin, Yong
    Chen, Jinqu
    Chen, Zhuo
    Du, Bo
    Li, Baowen
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2024, 637
  • [10] Measuring the resilience of an urban rail transit network: A multi-dimensional evaluation model
    Ma, Zhiao
    Yang, Xin
    Wu, Jianjun
    Chen, Anthony
    Wei, Yun
    Gao, Ziyou
    TRANSPORT POLICY, 2022, 129 : 38 - 50