Journal of South China University of Technology(Natural Science) >

2023 , Vol. 51 >Issue 6: 42 - 51

DOI: https://doi.org/10.12141/j.issn.1000-565X.220486

Traffic & Transportation Engineering

Resilience Evolution of Multi-mode Transportation Network in Urban Agglomeration Based on Risk Diffusion

Expand
  • 1.College of Transportation Engineering，Chang’an University，Xi’an 710064，Shaanxi，China
    2.Key Laboratory of Transport Industry of Management，Control and Cycle Repair Technology for Traffic Network Facilities in Ecological Security Barrier Area，Xi’an 710064，Shaanxi，China
马书红（1975-），女，教授，博士生导师，主要从事交通规划、交通安全研究。

Received date: 2022-08-01

  Online published: 2022-12-21

Supported by

the National Natural Science Foundation of China(51878062)

Fold

Abstract

It can help improve the risk resilience of urban agglomerations to carry out in-depth analysis of the dynamic resilience evolution characteristics of multi-modal transport networks in urban agglomerations during the risk diffusion phase. Based on complex network theory and its extension theory, this study constructed a multi-modal and multi-level transportation network model for urban agglomerations based on road, railway and air networks. It matched node degree and node betweenness with accessibility, and analyzed their static topological characteristics under risk diffusion. Based on the theory of cascading failure dynamics, it considered the initial risk level, risk warning threshold and risk resilience of nodes at different stages, and constructed a risk dynamic diffusion model based on the nodes and connected edge measures affecting risk diffusion. Considering the characteristics of structural and functional changes under risk shocks, the paper constructed a network structural and functional resilience measurement model, and the resilience performance of multi-modal transport networks was represented by their coupling values. Using the multi-modal transport network of the Guan-Zhong Plain urban agglomeration as the research object, the Python Networkx and Matlab network analysis tools were used to simulate and analyze the dynamic resilience evolution of the multi-modal transport network of the urban agglomeration during the risk diffusion phase with respect to different risk diffusion methods, network reliability, redundancy, robustness and node risk handling capacity coefficients. The results show that the model results are consistent with reality. The network resilience can be effectively enhanced by improving network reliability, redundancy, robustness and node risk handling. Compared to the risk diffusion approach based on the node measure, the risk diffusion approach based on the connected edge measure has greater impact on resilience performance, suggesting that the distribution of route hierarchy levels has a greater impact on the resilience performance of multimodal transport networks in urban agglomerations compared to the number of routes. The overall resilience of a multi-modal, multi-level transport network performs better than that of a single transport network.

Key words： traffic engineering; urban agglomeration; multi-mode transportation network; risk diffusion; resilience evolution

Cite this article

MA Shuhong, YANG Lei, CHEN Xifang . Resilience Evolution of Multi-mode Transportation Network in Urban Agglomeration Based on Risk Diffusion[J]. Journal of South China University of Technology(Natural Science), 2023 , 51(6) : 42 -51 . DOI: 10.12141/j.issn.1000-565X.220486

References

1 AKBARZADEH M， MEMARMARMONTAERIN S， SYBIL D，et al ．The role of travel demand and network centrality on the connectivity and resilience of an urban street system［J］．Transportation，2019，46（5）：1127-1141.
2 DENG Z P， HUANG D R， LIU J Y，et al ．An assessment method for traffic state vulnerability based on a cloud model for urban road network traffic systems［J］．IEEE Transactions on Intelligent Transportation Systems，2021，22（11）：7155-7168.
3 MUKESH M， YASHWANT B， DIGAMBAR S ．Analyzing the impact of floods on vehicular mobility along urban road networks using the multiple centrality assessment approach［J］．Risk and Uncertainty in Engineering Systems：Part A-Civil Engineering，2022，8（3）：05022001/1-12.
4 马超群，张爽，陈权，等 ．客流特征视角下的轨道交通网络特征及其脆弱性［J］．交通运输工程学报，2020，20（5）：208-216.
  MA Chaoqun， ZHANG Shuang， CHEN Quan，et al ．Characteristics and vulnerability of rail transit network based on perspective of passenger flow characteristics［J］．Journal of Traffic and Transportation Engineering，2020，20（5）：208-216.
5 LU Q C， ZHANG L， XU P C，et al ．Modeling network vulnerability of urban rail transit under cascading failures：a coupled map lattices approach ［J］．Reliability Engineering & System Safety，2022，221（7）：108320/1-13.
6 ZHAO M， WANG X L， PAN W H，et al ．The vulnerability analysis of the multi-layer air transport system［C］∥ Proceedings of the 5th International Conference on Transportation Information and Safety （ICTIS）．Liverpool：ICTIS，2019：956-962.
7 LIU J， LU H P， MA H，et al ．Network vulnerability analysis of rail transit plans in Beijng-Tianjin-Hebei region considering connectivity reliability ［J］．Sustainability，2017，9（8）：1479/1-17.
8 沈犁，张殿业，向阳，等 ．城市地铁-公交复合网络抗毁性与级联失效仿真［J］．西南交通大学学报，2018，53（1）：156-163，196.
  SHEN Li， ZHANG Dianye， XIANG Yang，et al ．Simulation on survivability and cascading failure propagation of urban subway-bus compound network［J］．Journal of Southwest Jiaotong University，2018，53（1）：156-163，196.
9 SONNAM J， GAO L， LIU F，et al ．Cascading failure with preferential redistribution on bus-subway coupled network［J］．International Journal of Modern Physics，2021，32（8）：2150103/1-11.
10 ZHANG L， WEN H Y， LU J，et al ．Exploring cascading reliability of multi-modal public transit network based on complex networks［J］．Reliability Engineering & System Safety，2022，221：108367/1-27.
11 MA F， LIU F， YUEN K F，et al ．Cascading failures and vulnerability evolution in bus-metro complex bilayer networks under rainstorm weather conditions［J］．International Journal of Environmental Research and Public Health，2019，16（3）：329/1-30.
12 宋英华，李玉枝，霍非舟，等 ．城区内涝条件下城市公交-地铁双层交通网络的脆弱性分析［J］．安全与环境工程，2021，28（2）：114-120.
  SONG Yinghua， LI Yuzhi， HUO Feizhou，et al ．Vulnerability of two-layer traffic network of bus and subway under waterlogging condition based on complex network theory［J］．Safety and Environmental Engineering，2021，28（2）：114-120.
13 QI Q Y， KWON K ．Exploring the characteristics of high-speed rail and air transportation networks in China：a weighted network approach［J］．Journal of International Logistics and Trade，2021，19（2）：96-114.
14 WANG B， SU Q， CHIN K S ．Vulnerability assessment of China-Europe railway express multimodal transport network under cascading failures［J］．Physic A：Statistical Mechanics and its Applications，2021，584：126359/1-14.
15 徐凤，朱金福，苗建军 ．基于复杂网络的空铁复合网络的鲁棒性研究［J］．复杂系统与复杂性科学，2015，12（1）：40-45.
  XU Feng， ZHU Jinfu， MIAO Jianjun ．The robustness of high-speed railway and civil aviation compound network based on the complex network theory［J］．Complex Systems and Complexity Science，2015，12（1）：40-45.
16 强添纲，赵明明，裴玉龙 ．城市多模式交通网络的复杂网络特性与鲁棒性研究［J］．交通信息与安全，2019，37（1）：65-71.
  QIANG Tiangang， ZHAO Mingming， PEI Yulong ．An analysis of characteristics of complex network and robustness in Harbin multi-mode traffic network［J］．Journal of Transport Information and Safety，2019，37（1）：65-71.
17 CHEN D J， FANG X F， LI Y，et al ．Three-level multimodal transportation network for cross-regional emergency resources dispatch under demand and route reliability［J］．Reliability Engineering & System Safety，2022，222：108461/1-14.
18 APARICIO J， ARSENIO E， HENRIQUES R ．Assessing robustness in multimodal transportation systems：a case study in Lisbon［J］．European Transport Research Review，2022，14（1）：28/1-18.
19 彭翀，陈思宇，王宝强 ．中断模拟下城市群网络结构韧性研究——以长江中游城市群客运网络为例［J］．经济地理，2019，39（8）：68-76.
  PENG Chong， CHEN Siyu， WANG Baoqiang ．Analyzing city network’s structural resilience under disruption scenarios：a case study of passenger transport network in the middle reaches of Yangtze river［J］．Economic Geography，2019，39（8）：68-76.
20 马书红，武亚俊，陈西芳 ．城市群多模式交通网络结构韧性分析——以关中平原城市群为例［J］．清华大学学报（自然科学版），2022，62（7）：1228-1235.
  MA Shuhong， WU Yajun， CHEN Xifang ．Structural resilience of multimodal transportation networks in urban agglomerations：a case study of the Guanzhong plain urban agglomeration network［J］．Journal of Tsinghua University （Science and Technology），2022，62（7）：1228-1235.
21 侯兰功，孙继平 ．复杂网络视角下的成渝城市群网络结构韧性演变［J］．世界地理研究，2022，31（3）：561-571.
  HOU Langong， SUN Jiping ．Evaluation of network structure resilience of Chengdu-Chongqing urban agglomeration from the perspective of complex networks［J］．World Regional Studies，2022，31（3）：561-571.
22 李成兵，张帅，杨志成，等 ．蓄意攻击下城市群客运交通网络级联抗毁性仿真［J］．交通运输系统工程与信息，2019，19（2）：14-21.
  LI Chengbing， ZHANG Shuai， YANG Zhicheng，et al ．Invulnerability simulation in urban agglomeration passenger traffic network under targeted attacks［J］．Journal of Transportation Systems Engineering and Information Technology，2019，19（2）：14-21.
23 李成兵，魏磊，李奉孝，等 ．基于攻击策略的城市群复合交通网络脆弱性研究［J］．公路交通科技，2017，34（3）：101-109.
  LI Chengbing， WEI Lei， LI Fengxiao，et al ．Study on vulnerability of city agglomeration compound traffic network based on attacks strategy［J］．Journal of Highway and Transportation Research and Development，2017，34（3）：101-109.
24 付焯，户佐安，邱忠权 ．新冠肺炎疫情影响下多式联运网络突发事件风险传导机理［J］．安全与环境学报，2021，21（5）：1933-1940.
  FU Chuo， LU Zuoan， QIU Zhongquan ．Research on the risk transmission mechanism of multimodal transportation networks under the impact of the COVID 19 outbreak［J］．Journal of Safety and Environment，2021，21（5）：1933-1940.
Options
Outlines

/

〈 〉