风险扩散下城市群多模式交通网络的韧性演化

马书红, 杨磊, 陈西芳

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

华南理工大学学报(自然科学版) >

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

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

交通运输工程

风险扩散下城市群多模式交通网络的韧性演化

展开

^1.长安大学运输工程学院，陕西西安 710064
^2.生态安全屏障区交通网设施管控及循环修复技术交通运输行业重点实验室，陕西西安 710064

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。

收稿日期: 2022-08-01

网络出版日期: 2022-12-21

基金资助

国家自然科学基金资助项目(51878062);陕西省交通厅科技项目(21-13R)

收起

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

摘要

深入分析风险扩散阶段城市群多模式交通网络的动态韧性演化特征，有助于提高城市群风险抵御能力。本研究基于复杂网络理论及其扩展理论，以城市群公路、铁路、航空网络为基础，构建城市群多模式多层次交通网络模型，将节点度、节点介数与可达性相匹配，分析其风险扩散下的静态拓扑特征；以级联失效动力学理论为基础，考虑不同阶段节点初始风险水平、风险预警阈值与风险抵御能力，根据影响风险扩散的节点与连边测度指标，构建风险动态扩散模型；考虑风险冲击下结构、功能变化特征，构建网络结构、功能韧性测度模型，并通过其耦合值表征多模式交通网络韧性性能。以关中平原城市群多模式交通网络为研究对象，运用Python Networkx和Matlab网络分析工具，就不同的风险扩散方式、网络可靠性、冗余性、鲁棒性和节点风险处理能力系数，对风险扩散阶段城市群多模式交通网络的动态韧性演化进行仿真分析。结果表明：模型结果与实际相符，提升网络可靠性、冗余性、鲁棒性和节点风险处理能力，能有效增强网络韧性；相较于基于节点测度的风险扩散方式，基于连边测度的风险扩散方式对韧性性能影响更大，说明线路层次等级分布相较于数量对城市群多模式交通网络的韧性性能影响更大；相较于单一的交通网络，多模式多层次的交通网络韧性性能整体表现更佳。

关键词： 交通工程; 城市群; 多模式交通网络; 风险扩散; 韧性演化

本文引用格式

马书红, 杨磊, 陈西芳 . 风险扩散下城市群多模式交通网络的韧性演化[J]. 华南理工大学学报(自然科学版), 2023 , 51(6) : 42 -51 . DOI: 10.12141/j.issn.1000-565X.220486

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

参考文献

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

文章导航

模态框（Modal）标题

摘要

本文引用格式

Abstract

参考文献