摘要
现有关于城市轨道交通网络(URTN)的网络特性及鲁棒性研究多数选择建立无权模型,在反映网络结构特征上具有局限性。基于复杂网络理论和Space-L方法,提出考虑城市轨道线路实际距离值以及站点间线路数量干扰的URTN加权模型,并以武汉市轨道交通网络为例进行网络特性及级联失效鲁棒性实证分析。结果表明:与无权网络相比,武汉轨道交通加权网络的网络结构更加紧密,节点间的联通程度更优,该网络同时具备小世界网络特性和无标度网络特性;武汉轨道交通加权网络在面对随机攻击时表现出一定的鲁棒性,面对多组蓄意攻击时鲁棒性较差,在考虑负载重分配的级联失效情况下交通网络呈现更强的脆弱性;重要站点失效对网络的破坏程度更高,保护重要站点以及合理设置站点容量可以有效增强网络整体的抗毁能力,保障整个URTN的安全运营。
Most of the existing research on the network characteristics and robustness of urban rail transit network(URTN)choose to establish the unauthorized model,which has limitations in reflecting the network structure characteristics.Based on the theory of complex network and Space-L method,this thesis proposed the URTN weighted model considering the actual distance value of urban rail lines and the interference of the number of lines between stations,and took the Wuhan rail transit network as an example to conduct an empirical analysis of network characteristics and cascading failure robustness.The results show that compared with the unauthorized network,the network structure of the Wuhan rail transit weighted network is closer and the connectivity between nodes is better,the network has both small-world and scale-free characteristics;The weighted network of Wuhan rail transit shows certain robustness in the face of random attacks,but poor robustness in the face of multiple deliberate attacks,and stronger vulnerability in the case of cascade failures considering load distribution;The failure of important sites will damage the network to a higher degree.Protecting important sites and setting the site capacity reasonably can effectively enhance the overall anti-damage ability of the network and guarantee the safe operation of the whole URTN.
作者
詹斌
袁野
杨世武
盛涛
ZHAN Bin;YUAN Ye;YANG Shiwu;SHENG Tao(School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China;不详)
出处
《武汉理工大学学报（信息与管理工程版）》
2022年第6期917-923,929,共8页
Journal of Wuhan University of Technology：Information & Management Engineering
关键词
城市轨道交通
加权网络
网络特性
级联失效
鲁棒性
urban rail transit
weighted network
network characteristic
cascading failure
robustness
