台北捷運是雙北市民通勤交通工具之首選，但這樣的城市軌道交通系統往往
可能因不同原因需中斷服務，不管是系統異常、人為事件（例如台北捷運隨機殺
人案件）或者自然災害（例如地震），都可能導致捷運停駛或者運量下降，若能
提早準備，讓捷運系統在意外發生時能夠快速反應，則能減少損失。本研究考量
捷運系統的拓撲架構以及路網中不同站點間的乘客流量建構出用以評估捷運路
網及站點脆弱度（ vulnerability）的指標，並且分析在隨機故障及蓄意攻擊下捷運
系統之效能，研究中除了由站點失效的觀點確 認路網中的重要站點之外，當採用
路線觀點進行評估時，亦發現淡水信義線因為高旅客流量、高站點數、站點重要
性高，因而被攻擊時導致整條路線停駛之脆弱度最高。本研究結果可做為捷運公
司或交通管理單位之決策參考，針對這些高脆弱度的站點 /路線加強防護，以提高
捷運系統的穩健性。

Taipei Mass Rapid Transit (Taipei MRT) is considered the most important transportation system for commuters in Taipei and New Taipei cites. However, the urban rail transit systems like Taipei MRT may often be interrupted for different reasons. System anomalies, human events (e.g., the Taipei MRT random killing case) or natural disasters (e.g., earthquakes) may all cause the MRT operation to stop or cause the traffic volume to drop. This study analyzes the vulnerability of Taipei MRT from both station and line operation perspective. In particular, not only the network topology structure of the MRT system but also the passenger flow between different stations were considered to construct indicators for evaluating the system and stations vulnerability, and the effectiveness of MRT system under the random failure and deliberate attacks. Results show that Taipei MRT system is the most vulnerable when Red line is attacked and entire line is out of operation because of its high passenger flow, high number of stations, and high critical stations. Results and the important managerial implication of this study may be used by managers or policy makers in relevant department to improve the reliability and robustness of the public transportation services.

Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. science, 286(5439), 509-512.
Berdica, K. (2002). An introduction to road vulnerability: what has been done, is done and should be done. Transport policy, 9(2), 117-127.
Chopra, S. S., Dillon, T., Bilec, M. M., & Khanna, V. (2016). A network-based framework for assessing infrastructure resilience: a case study of the London metro system. Journal of The Royal Society Interface, 13(118), 1-11.
Chen, W., Li, Z., Ai, Y., & Ju, Y. (2018, October). Research on Reliability of Chengdu Rail Transit Network Based on Complex Network Theory. In International Conference on Smart Vehicular Technology, Transportation, Communication and Applications(pp. 201-207). Springer, Cham.
Derrible, S., & Kennedy, C. (2010). The complexity and robustness of metro networks. Physica A: Statistical Mechanics and its Applications, 389(17), 3678-3691.
De-Los-Santos, A., Laporte, G., Mesa, J. A., & Perea, F. (2012). Evaluating passenger robustness in a rail transit network. Transportation Research Part C: Emerging Technologies, 20(1), 34-46.
Du, Y., Gao, C., Hu, Y., Mahadevan, S., & Deng, Y. (2014). A new method of identifying influential nodes in complex networks based on TOPSIS. Physica A: Statistical Mechanics and its Applications, 399, 57-69.
Erdős, P.; Rényi, A. (1959). On Random Graphs, I. Publicationes Mathematicae. 6: 290–297.
Faturechi, R., & Miller-Hooks, E. (2014). Measuring the performance of transportation infrastructure systems in disasters: A comprehensive review. Journal of infrastructure systems, 21(1), 04014025, 1-15.
Latora, V., & Marchiori, M. (2001). Efficient behavior of small-world networks. Physical review letters, 87(19), 198701, 1-4.
Hong, L., Yan, Y., Ouyang, M., Tian, H., & He, X. (2017). Vulnerability effects of passengers' intermodal transfer distance preference and subway expansion on complementary urban public transportation systems. Reliability Engineering & System Safety, 158, 58-72.
Mattsson, L. G., & Jenelius, E. (2015). Vulnerability and resilience of transport systems–A discussion of recent research. Transportation Research Part A: Policy and Practice, 81, 16-34.
Newman, M. (2010). Networks: An Introduction. Oxford University Press.
Rodríguez-Núñez, E., & García-Palomares, J. C. (2014). Measuring the vulnerability of public transport networks. Journal of transport geography, 35, 50-63.
Sun, D. J., & Guan, S. (2016). Measuring vulnerability of urban metro network from line operation perspective. Transportation Research Part A: Policy and Practice, 94, 348-359.
Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-world’networks. nature, 393(6684), 440-442.
黃傳楷 , & 王聖鐸 . (2017). 臺北捷運路網結構之脆弱度分析 . 地理研究 , (66), 1-16.
謝承憲 , 馮正民 , & 柯旻嬋 . (2014). 構建都會區運輸路網脆弱度評量模式 . 運輸
學刊 , 26(3), 349-372.
謝承憲 , 馮正民 , & 賴怡心 . (2015). 臺灣西部城際旅客運輸路網脆弱度之評估模
式 . 都市與計劃 , 42(4), 367-388.
政府資料開放平台 -臺北捷運各站進出量統計。網址 :https://data.gov.tw/dataset/61753。 上網時間 :2019/4/28。
政府資料開放平台 -臺北捷運系統相鄰兩站間之行駛時間、停靠站時間。網址 : https://data.gov.tw/dataset/61792。 上網時間 :2019/4/28。