Identification of Key Stations and Routes in Urban Metro and Conventional Bus Networks from a Resilience Perspective
SUN Xiaohuia, LIU Yib, MI Yumeib, LÜ Kaib
a. School of Traffic and Transportation Engineering, Xinjiang Key Laboratory of Green Construction and Smart Traffic Control of Transportation Infrastructure;b. College of Civil Engineering and Architecture, Xinjiang University, Urumqi 830017, China
Abstract：Urban Metro and conventional bus carry a significant portion of residents' daily travel services, and their disruption due to sudden incidents often results in widespread and profound impacts. To ensure safe and efficient operation of public transportation, based on complex network theory, a method is proposed from the perspective of structural resilience for identifying key stations and routes of urban metro and conventional bus networks through importance, that is the resilience-based mean square deviation-TOPSIS comprehensive evaluation method. The reliability of this method is respectively verified through the monotonicity of the importance evaluation results, the robustness analysis of different attack strategies, and the comparative analysis of construction timelines. The case study results show that this method can well differentiate each station in the network; when conducting robustness analysis, it can also reflect the characteristic that key stations with greater importance have a larger impact on the overall network performance; the K-means clustering results of the importance of Shenzhen metro lines are generally consistent with the construction timeline. The reliability of this method in identifying key stations and routes is verified comprehensively.
孙小慧, 刘毅, 米玉梅, 吕凯. 韧性视角下城市地铁与常规公交网络关键站点及线路识别[J]. 复杂系统与复杂性科学, 2026, 23(1): 26-36.
SUN Xiaohui, LIU Yi, MI Yumei, LÜ Kai. Identification of Key Stations and Routes in Urban Metro and Conventional Bus Networks from a Resilience Perspective[J]. Complex Systems and Complexity Science, 2026, 23(1): 26-36.
[1] 高德地图. 2021年度中国主要城市交通分析报告[R/OL]. (2022-01-19)[2023-11-20].https://report.amap.com. GAODE MAP. 2021 traffic analysis report of major chinese cities[R/OL]. (2022-01-19)[2023-11-20]. https://report.amap.com. [2] 韩月一, 王登忠, 王如杰, 等. 城市地铁站点接驳公交多目标优化方法[J]. 交通运输工程与信息学报, 2023, 21(1): 80-93. HAN Y Y, WANG D Z, WANG R J, et al. Multi-objective optimization method for connecting buses in urban subway stations [J]. Journal of Transportation Engineering and Information, 2023, 21(1): 80-93. [3] 林忠义. 城市多模式公共交通网络特性分析及优化研究[D]. 长春: 吉林大学, 2022. LIN Z Y. Characteristic analysis and optimization of urban multi-modepublic transport network[D]. Changchun: Jilin University, 2022. [4] XIONG J, CHEN B, HE Z B, et al. Optimal design of community shuttles with an adaptive-operator-selection-based genetic algorithm[J]. Transportation Research Part-C-Emerging Technologies, 2021, 126: 103109. [5] 贾慧慧. 常规公交与轨道交通共线条件下的运营协调优化研究[D]. 北京: 北京交通大学, 2022. JIA H H. Research on the optimization of operation coordinationunder collinear condition of bus and rail transit[D]. Beijing: Beijing Jiaotong University, 2021. [6] 董宇飞. 基于改进免疫遗传算法的城轨交通与常规公交衔接研究[D]. 大连: 大连交通大学, 2020. DONG Y F. Research on the optimization of operation coordinationunder collinear condition of bus and rail transit[D]. Dalian: Dalian Jiaotong University, 2021. [7] 张广亮. 基于复杂网络的城市路网韧性提升策略研究[D]. 哈尔滨: 哈尔滨工业大学, 2021. ZHANG G L. Research on strategys of urban road network resilience improvement based on complex network[D]. Harbin: Harbin Institute of Technology, 2021. [8] AKBARZADEH M, MEMARMONTAZERIN S, DERRIBLE S, et al. The role of travel demand and network centrality on the connectivity and resilience of an urban street system[J]. Transportation, 2019, 46(4): 1127-1141. [9] 马书红, 武亚俊, 陈西芳. 城市群多模式交通网络结构韧性分析——以关中平原城市群为例[J]. 清华大学学报(自然科学版), 2022, 62(7): 1228-1235. MA H S, WU Y J, CHEN X F. Structural resilience of multimodal transportation networks in urban agglomerations:a case study of the Guanzhong Plain urban agglomeration network[J]. Journal of Tsinghua University(Science and Technology), 2022, 62(7): 1228-1235. [10] 陈丹, 钟玉刚, 尹嘉男, 等. 扰动事件影响下城市轨道交通网络风险评价[J]. 武汉理工大学学报(交通科学与工程版), 2023, 47(6): 1042-1047. CHEN D, ZHONG Y G, YIN J N, et al. Risk assessment for urban rail transit network under disruption events[J]. J Journal of Wuhan University of Technology(Transportation Science & Engineering), 2023, 47(6): 1042-1047. [11] JING W, XU X, PU Y. Route redundancy-based network topology measure of metro networks[J]. Journal of Advanced Transportation, 2019, 2019: 1-12. [12] 马书红, 杨磊, 陈西芳. 风险扩散下城市群多模式交通网络的韧性演化[J]. 华南理工大学学报(自然科学版), 2023, 51(6): 42-51. MA H S, YANG L, CHEN X F. Resilience evolution of multi-mode transportation network in urban agglomeration based on risk diffusion[J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(6): 42-51. [13] 谌微微, 张富贵, 赵晓波. 轨道交通线网拓扑结构模型及节点重要度分析[J]. 重庆交通大学学报(自然科学版), 2019, 38(7): 107-113. ZHAN W W, ZHANG F G, ZHAO X B. Topological structure model and node importance analysis of rail transit network[J]. Journal of Chongqing Jiaotong University(Natural Sciences), 2019, 38(7): 107-113. [14] 任广建, 张明, 郭宇帅. 基于拉普拉斯能量相对熵的航路网络节点重要性评估分析[J]. 北京交通大学学报, 2023, 47(2): 76-85. REN G J, ZHANG M, GUO Y S. Node importance evaluation in air route networks based on Laplacian energy relative entropy[J]. Journal of Beijing Jiaotong University, 2023, 47(2): 76-85. [15] 王淑良, 陈辰, 张建华, 等. 基于复杂网络的关联公共交通系统韧性分析[J]. 复杂系统与复杂性科学, 2022, 19(4): 47-54. WANG S L, CHEN C, ZHANG J H, et al. Resilience analysis of public interdependent transport system based on complex network[J]. Complex Systems and Complexity Science, 2022, 19(4): 47-54. [16] 冯芬玲, 蔡明旭, 贾俊杰. 基于多层复杂网络的中欧班列运输网络关键节点识别研究[J]. 交通运输系统工程与信息, 2022, 22(6): 191-200. FENG F L, CAI M X, JIA J J. Key node identification of China railway express transportation network based on multi-layer complex network[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 191-200. [17] 邵春福. 交通规划原理[M]. 2版. 北京: 中国铁道出版社, 2020: 322. [18] 林兆丰, 李树彬, 孔祥科. 地铁建设对公交系统鲁棒性的影响[J]. 复杂系统与复杂性科学, 2023, 20(1): 66-73. LIN Z F, LI S B, KONG X K. The influence of subway construction on the robustness of public transportation system[J]. Complex Systems and Complexity Science, 2023, 20(1): 66-73. [19] 百度百科. 深圳地铁16号线[DB/OL]. (2011-7-16)[2024-01-07]. https://baike.baidu.com/item/%E6%B7%B1%E5%9C%B3%E5%9C%B0%E9%93%8116%E5%8F%B7%E7%BA%BF/10161323. BAIDU BAIKE. Shenzhen metro line 16[DB/OL]. (2011-7-16)[2024-01-07]. https://baike.baidu.com/item/%E6%B7%B1%E5%9C%B3%E5%9C%B0%E9%93%8116%E5%8F%B7%E7%BA%BF/10161323. [20] 薛锋, 何传磊, 黄倩. 成都地铁网络的关键节点识别方法及性能分析[J]. 中国安全科学学报, 2019, 29(1): 93-99. XUE F, HE C L, HUANG Q. Identification of key nodes in Chengdu metro network and analysis of network performance[J]. China Safety Science Journal, 2019, 29(1): 93-99.
