大客流冲击下北京市轨道交通网络稳定性
Stability of Beijing rail transit network under the impact of large passenger flow

为了减少轨道交通站点运营不稳定现象的发生，优化轨道交通网络结构，提升网络运营效率，对大客流冲击下的轨道交通运行稳定性进行研究。以北京市轨道交通网络为例，采用L空间法构建以轨道站点为节点、相邻站点线路为连边的北京市轨道交通网络模型；仿真分析了节点度、平均路径长度、聚类系数、网络直径、网络效率等特征参数值和其分布规律。根据事件类型将站点分为功能减弱站点和功能中断站点，并分别采用客流传播模型和网络效率模型，仿真量化了不同事件类型发生背景下的网络稳定性。研究结果表明：现阶段北京市轨道交通网络具有无标度网络的特征，网络可达性较好，聚类系数较小，网络连通性有待提高；当换乘站因超大客流出现而功能减弱时，若相邻站点数S≤7时，网络中拥挤站点拥挤状态可自行消退，且相邻站点数与拥挤消退所需时间呈负相关；当换乘站出现功能中断时，网络效率值会显著降低，破坏站点的重要度系数在(0.75,1］范围时对网络效率的影响最大，在（0,0.5］范围时对网络效率的影响最小。该研究结果为及时发现轨道网络关键点及其薄弱环节，保障超大客流背景下的城市轨道交通网络安全运营提供依据，也为大客流冲击下的北京市轨道网络应急方案的制定提供决策支持。
In order to reduce the operation instability of rail transit station, optimize the structure of rail transit network and improve the efficiency of network operation, the stability of rail transit operation under the impact of large passenger flow was studied. Taking Beijing rail transit network as an example, Beijing rail transit network model with rail stations as nodes and adjacent stations as edges was constructed by using Space L method. The characteristic parameters and distribution rules of node degree, average path length, clustering coefficient, network diameter and network efficiency were simulated and analyzed. According to the type of accidents, these stations were divided into site operation weakened and operation disrupted, respectively. Base on passenger-flow propagation model and network efficiency model, the simulation quantified the network stability under the background of different event types. The results show that Beijing rail transit network is a scale-free network. The accessibility of rail transit network is better and clustering coefficient of it is small，but connectivity of it should be improved. And when site operation is weakened because of the large passenger flow in Beijing transit network, if the number of adjacent station is not more than 7, passenger-flow propagation state in network can regress, or negative correlation is observed between the number of adjacent station and the fading time. When transfer station is disrupted, the value of network efficiency will decrease significantly. The importance coefficient of the damaged site has the greatest impact on network efficiency in the range of (0.75,1], and the least in the range of (0,0.5]. The research results provide a basis for timely finding the key points and weak links of rail network, ensuring the safety operation of urban rail transit network under the background of super passenger flow, and providing a decision support for the development of emergency plan of Beijing rail transit network under the impact of large passenger flow