Abstract: To realize the practical value of historical earthquake data in the seismic resilience assessment of urban rail transit networks (URTNs), it is necessary to establish links between resilience assessment and real-world factors, including network topological characteristics, service coverage capacity, passenger flow characteristics, the spatial distribution of earthquakes, and the vulnerability of civil infrastructure, thereby improving the fidelity of resilience assessment. Taking Shanghai as an example, this study first established a ground-motion calculation model considering historical earthquake data and a vulnerability model for civil infrastructure. These models were then embedded into the URTN topology model, and their coupling was achieved by controlling the failure states of nodes and links in the topology model under earthquake scenarios. For resilience calculation and assessment, fractal dimension was computed using information dimension theory and taken as the functional indicator of network resilience, while the resilience triangle was used to characterize the variation of network resilience over time. Subsequently, this method was applied to obtain the resilience assessment results of Shanghai URTN: Before the earthquake, the fractal dimension was approximately 1.2. Under M_s 3.0 and M_s 4.0 earthquakes, the fractal dimension showed no obvious change. Under M_s 5.0 and M_s 6.0 earthquakes, however, the fractal dimension exhibited significant attenuation, and the corresponding recovery times were 3,400 h and 5,000 h, respectively, both indicating severe resilience losses. After preventive reinforcement measures were implemented, the Shanghai URTN was able to maintain an essentially normal operational state under M_s 5.0 earthquakes. Under M_s 6.0 earthquakes, the post-earthquake recovery time was shortened by about 30%, and the resilience loss was reduced by about 34%. The results show that using fractal dimension for seismic resilience assessment can incorporate more real-world elements and comprehensively and quantitatively evaluate the performance and resilience characteristics of URTNs before and after earthquake disasters. Preventive reinforcement measures can also significantly improve the seismic resilience of URTNs.