考虑站点韧性的轨道交通网络级联失效研究OA
Cascading failure of rail transit network considering station resilience
随着城市轨道交通网络的不断扩展与客流增长,网络中节点之间高度耦合的特性使得单个站点故障可能引发级联失效.为模拟网络在突发事件扰动下的级联失效演化过程,并量化评估站点韧性因素对失效传播的抑制作用,基于标准Sigmoid函数思想构建站点抵抗能力影响函数,设计考虑站点特性的车站节点修复规则.在传统耦合映像格子模型基础上提出融合客流强度、站点抵抗与恢复能力的改进耦合映像格子模型,结合南京市地铁网络与自动售检票系统客流数据,进行模型有效性与关键参数敏感性分析,并模拟不同耦合参数与扰动场景下的级联失效演化过程.研究结果表明:1)相较于传统耦合映像格子模型与考虑拓扑加权与客流加权的耦合映像格子模型,融入站点韧性因素的改进模型在模拟轨道交通网络级联失效过程中,能够更准确地反映站点自身的抵抗与恢复能力对失效传播的影响;2)网络遭受蓄意攻击引发的级联失效比随机攻击更为严重,且拓扑与客流耦合系数的变化会显著影响失效传播规模,换乘枢纽站点在失效扩散与恢复过程中发挥着关键作用;3)高韧性站点能够有效减缓失效传播的速度,高效的恢复措施有助于减少最大失效节点数量并缩短全网恢复时间.研究结果可为地铁相关部门在车站选址与设施建设中强化抗风险能力提供理论依据,并为制定高效故障恢复策略与提升网络可靠性提供参考.
Urban rail transit networks are expanding with passenger flow increasing.This creates high coupling between nodes,a single site failure may cause cascading failure.In order to simulate the cascading failure evolution process within the network under the disturbance of emergencies and to quantitatively assess the inhibitory effect of station resilience factors on failure propagation,a station-resistance influence function based on the standard Sigmoid was constructed.The repair rules of station nodes considering site characteristics were designed.Based on the traditional coupled map lattice(CML)model,an improved CML model integrating passenger flow intensity,site resistance and recovery ability was proposed.Combined with the passenger flow data from Nanjing metro line network and Automatic Fare Collection System,the effectiveness and sensitivity of key parameters in the proposed model were analyzed.The cascading failure evolution process under different coupling parameters and disturbance scenarios was simulated as well.The results are shown as follows.1)During the failure propagation in the simulation of the cascading failure process within urban rail transit network,the improved CML model incorporating the station resilience factors can more accurately reflect the influence of the site resistance and recovery ability compared to the traditional CML model as well as the CML models weighted by the topology and passenger flow.2)The cascading failure caused by intentional attack is more serious than random attack,the change of topology and passenger flow coupling coefficient significantly affect failure spread scale.Besides,the transfer hub station plays a key role in the process of failure diffusion and recovery.3)High resilience stations can effectively slow down the scope and speed of failure propagation,and effective recovery measures can help reduce the maximum number of failed nodes as well as the shorten overall network recovery time.The results can provide theoretical support for the metro authorities to enhance the risk-resistance capabilities in station location and facility construction.It can also offer a reference for formulating efficient fault recovery strategies and improving network reliability.
叶茂;孙康宁;唐坤;毕廉杰;何赏璐
南京理工大学 自动化学院,江苏 南京 210094南京理工大学 自动化学院,江苏 南京 210094南京理工大学 自动化学院,江苏 南京 210094南京理工大学 自动化学院,江苏 南京 210094南京理工大学 自动化学院,江苏 南京 210094
交通工程
城市轨道交通级联失效站点韧性改进耦合映像格子模型复杂网络理论
urban rail transitstation resilienceimproved coupled map lattice modelcascading failurecomplex network theory
《铁道科学与工程学报》 2026 (5)
2132-2142,11
国家重点研发计划课题(2017YFB1201202)江苏省交通运输科技项目(2023G05)
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