非均衡大客流冲击下城市轨道交通网络抗毁性建模及演化特征

Modeling and evolution characteristics of urban rail transit network resistance under the impact of unbalanced large passenger flows

在非均衡大客流冲击下,城市轨道交通面临结构抗毁和功能抗毁双重压力,极易造成轨道交通网络级联失效。首先,该文分析了非均衡大客流对城市轨道交通网络(urban rail transit network,URTN)级联失效的影响机理,考虑客流冲击影响,构建了客流加权网络,从拓扑特征和客流特征2方面测量轨道站点的重要性;其次,根据级联失效理论和混沌动力学改进耦合映像格子(coupled map lattice,CML)模型,设置初始状态值为轨道站点客流饱和程度,并利用故障节点比和网络强度熵刻画URTN级联失效的结构抗毁性和功能抗毁性演化规律;最后,以西安地铁为例进行研究。结果表明:在URTN级联失效过程中,结构抗毁性和功能抗毁性演化趋势相似;轨道站点间的耦合系数ε和突发事件扰动R存在临界值(ε=0.3和R=1),若ε≤0.3或R≤1,则不发生URTN级联失效,若ε>0.3且R>1,则URTN结构抗毁性和功能抗毁性的失效时间随ε和R的增大而缩短;客流强度与URTN抗毁性水平呈负相关;介数大的轨道站点和客流强度大的轨道站点受突发扰动后,URTN结构抗毁性和功能抗毁性能力更低。该文研究结果有助于揭示非均衡大客流冲击下URTN级联失效的影响因素及抗毁性演化规律,可为加强非均衡大客流冲击下轨道交通安全管理提供依据。

[Objective]Despite unbalanced large passenger flows,urban rail transit network(URTN)frequently encounter the dual pressures of structural and functional resistance.This can result in cascade failure,potentially leading to partial or even total collapse of the URTN.To ensure the normal operation of these networks and understand the characteristics of their disaster resistance evolution,this study explores how an unbalanced large passenger flow affects the disaster resistance of URTN.[Methods]This study initially examines the effect of unbalanced large passenger flows on the URTN cascade failure from two perspectives:transport efficiency and passenger service.Subsequently,a passenger-flow weighting network is constructed to calculate the passenger-flow intensity.Herein,the weights of different nodes represent the proportion of the passenger flow per unit of time at different track stations during periods of unbalanced large passenger flows.This allows the measurement of a track station's importance level based on node number,node betweenness,and passenger flow intensity.Moreover,this study adapts the coupled map lattice(CML)model,building upon cascade failure theory and chaos dynamics,to obtain more accurate values for the failure node ratio and network strength entropy.In the modified CML model,the sudden disturbance level is defined according to the breakdown degree and influence range.The initial state value is determined by the saturation degree of the passenger flow at the track station,thus addressing the sensitive dependence of the spatiotemporal chaotic system on the initial state value.Subsequently,the dynamic evolution characteristics of the URTN structural and functional resilience levels are explored under different conditions of fault propagation and passenger flow strength.These analyses were based on failure node ratio and network strength entropy metrics.Finally,a case study was conducted using the Xi'an subway as an example.[Results]The results showed the following:(1)During a URTN cascade failure,the disaster resistance evolution trends of structure and function aligned,changed,and failed simultaneously.(2)Critical values existed for the inter-station coupling coefficientεand sudden event disturbance R,which wereε=0.3 and R=1,respectively.Below these thresholds,the URTN cascade failure effect did not occur.However,whenε>0.3 and R>1,the failure time of the URTN's structural and functional disaster resistance decreased asεand R increased.(3)The intensity of the passenger flow negatively affected the structural and functional resilience of the URTN.When disturbed,stations with high passenger flow intensity were more likely to trigger a URTN cascade failure.(4)Stations with large interconnectors and high passenger flow intensity exhibited lower structural and functional vulnerability after a sudden disturbance than stations with larger degrees.[Conclusions]This study has important theoretical and practical implications.Theoretically,it helps uncover the factors affecting cascade failure and the evolution characteristics of the URTN's disaster resistance under the impact of an unbalanced large passenger flows.In practice,this study provides a crucial foundation for decision-making regarding the enhancement of safety management in rail transit when faced with challenges posed by unbalanced large passenger flows.