交通运输网络韧性研究现状及展望

doi:10.13229/j.cnki.jdxbgxb.20250385

摘要/Abstract

摘要：

为厘清交通运输网络韧性的研究脉络，对国内外相关研究进行了系统综述。在网络模型构建上，总结了单一和多种运输方式网络建模方法；针对交通运输网络韧性评估，梳理了基于网络指标、基于网络性能、基于仿真模拟和基于数据驱动的韧性评估方法；针对韧性提升策略，从预防策略、应急策略和恢复策略3个方面总结了交通网络韧性提升措施并归纳了常用的优化模型及算法。最后，对交通运输网络韧性的研究现状进行评述并提出了该领域的未来研究方向。

关键词: 交通运输系统工程, 交通运输网络, 研究综述, 韧性评估, 韧性提升

Abstract:

In order to clarify the research context of transportation network resilience， a systematic review of domestic and international studies was provided， covering three key dimensions： network modeling， resilience assessment， and enhancement strategies. For network model construction， modeling methods for single-mode and multimodal transport networks were analyzed. Regarding the resilience assessment for transportation networks， a resilience assessment indicator system was sorted out， consisting of network topology indicators， operation indicators and attribute indicators. And four resilience assessment methods were summarized， including network indicator analysis， network performance curve evaluation， simulation modeling and data-driven techniques. Concerning resilience enhancement strategies， enhancement measures were systematically categorized into prevention， emergency response， and recovery strategies， with corresponding optimization models and algorithms summarized. Finally， the current research status of transportation network resilience was reviewed and the further research directions in this field were proposed in terms of specific disruption scenario simulation， resilience optimization strategies and multimodal transport network resilience.

Key words: engineering of communications and transportation system, transportation networks, research review, resilience assessment, resilience improvement

中图分类号:

U113

张玉召,丁欣茹,侯长啸,陈虎林. 交通运输网络韧性研究现状及展望[J]. 吉林大学学报(工学版), 2026, 56(3): 585-602.

Yu-zhao ZHANG,Xin-ru DING,Chang-xiao HOU,Hu-lin CHEN. Research status and prospects of resilience for transportation networks[J]. Journal of Jilin University(Engineering and Technology Edition), 2026, 56(3): 585-602.

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构建方法	构建形式	适用场景	相关文献
Space L	将交通站点和港口抽象为节点，直接连接的交通线路表示为边	针对不同节点在网络中的相互作用或网络结构的相关研究	Zhang等^［6］，Xu等^［7］，冯芬玲等^［8］
Space P	将交通站点和港口抽象为节点，同一线路上的节点用边相连	针对网络中节点可达性或中转节点的研究	冯芬玲等^［8］，Jiao等^［9］，Zhang等^［10］
Space C	将线路作为节点，共享站点的线路间建立连接	用于研究网络中线路之间的相关关系	何佳明^［11］，叶森等^［12］

交通运输网络	韧性评估指标	相关文献
城市道路交通网络	路网效率（路网流量分布状态）	吕彪等^［26］
高速公路网络	网络拓扑结构、动态交通流时空特性、道路基础设施类型	徐鹏程等^［27］
城市轨道交通网络	地铁客流量恢复正常的速度；	D'Lima等^［28］
城市轨道交通网络	站间旅客人数、加权平均出行时间	Chen等^［29］
铁路客运网络	网络效率、最短出行时间、最短出行距离（网络性能指标）	吴鹏等^［30］
海运港口网络	灾害前、后港口吞吐量之比	Li等^［31］
机场基础设施网络	航班数量、载客量（网络服务效率函数）	黄信等^［32］

属性特征	含义	度量方法
预防性（Preparedness）	在网络受干扰前做好准备，尽可能减少网络攻击受到的影响，提升抗干扰能力	基于网络拓扑指标^［7］；采取预防措施前后的网络性能水平
冗余性（Redundancy）	网络受干扰后能提供可替代服务，维持可接受性能的能力	节点间可用备选路径的数量^［36］
鲁棒性（Robustness）	承受或吸收干扰，面对干扰时维持正常功能的能力	受干扰后系统的剩余性能水平^［7］；干扰后与干扰前网络性能比值^［36］
适应性（Resourcefulness）	网络通过自行调整，以应对、管理和适应风险扰动^［38］	受干扰后重新分配货流、转换运输方式的能力（使用贝叶斯网络概率建模和量化^［39］）
快速恢复性（Rapid recovery）	通过采取修复措施，网络快速高效恢复到正常状态的能力	网络从受损状态恢复到初始状态的时间；一定修复资源或一定时间下网络性能的恢复程度

韧性量化形式	应用	特点
网络受干扰前、后指标变化情况→韧性值	拓扑指标变化情况^［22］、需求满足比率^［23］	指标选取较为片面，无法全面度量网络韧性值
韧性→不同维度网络功能属性	预防性、鲁棒性、互操作性^［7］，吸收能力、缓冲能力、恢复能力^［41］	区分了不同阶段的韧性能力；未能对网络整体韧性量化评估
不同指标分配权重加权求和→韧性值	需求满足比率和运输费用比率加权求和^［24］，吸收能力、缓冲能力和恢复能力加权求空间向量模^［41］	将所有指标综合为一个指标；存在主观因素的影响

失效传播模型	建模思路	应用案例
负载-容量级联失效模型	通过节点负载与容量的关系界定节点状态，模拟负载重分配导致的级联失效	城市群客运复合网络^［16］；中欧海铁运输网络^［17］；工程物流网络级联失效模型^［55］
耦合映像格子模型（Coupled map lattice， CML）	定义节点间耦合作用机制，通过节点状态迭代反映级联失效的动态传播^［56］	基于拥堵传播的CML模型^［46］；客流强度加权的CML模型^［57］；考虑节点抵抗特性H的HCML模型^［58］；考虑道路抵抗拥堵能力的M-CML模型^［59］
传播动力学模型	借鉴疾病传播理论，模拟风险在交通网络中的扩散与恢复过程；节点状态分为易染态（Susceptible，S）、感染态（Infected，I）和恢复态（Recovered，R）^［60］	港口风险传播SIS模型^［61］；多式联运网络风险传播SIRS模型^［62］
灾害蔓延动力学模型	结合节点自修复能力和灾害扩散机制，分析网络在干扰下的演化与稳定性	城市路网灾害演化^［63］；多式联运网络风险传播^［64］
基于渗流理论的风险传播机理	类比流体扩散过程，分析负载流动与节点/边状态变化的相互作用，最终达到平衡态	城市道路网络拥堵传播^［65］；不同拥堵率下城市交通网络性能状态^［66］；多式联运风险传播^［67］