Impact of Transportation Network Development on Service Resilience: Insights from Beijing

Urban rail transit (URT) networks can evolve substantially over time, with an increasing number and complexity of interactions between network components. In such networks, seemingly small disruptions can trigger cascading network service failures, affecting commuter comfort and experience. This study seeks to address the resilience of URT networks to service disruptions by understanding network evolution for resilience planning. Specifically, it develops the Network Resilience Assessment Framework (NRAF) to assess whether URT network structures are inherently resilient to service disruptions over time. The NRAF was applied to Beijing Subway data to evaluate the correlation between network evolution and service resilience. Key network evolution metrics, such as station line degree, clustering, and scaling factors, were analyzed to determine their impact on service resilience. The findings indicate that service resilience is correlated with the network's evolution. Both a high station line degree and clustering contribute to absorbing the impacts of service disruptions, while lower scaling factors are associated with higher annual average service resilience. The results suggest that promoting URT networking is an effective strategy for mitigating the impact of service disruptions. The study provides evidence that enhancing resilience can be achieved by fostering a more densely connected network and by decentralizing and reducing hierarchical differences at the global network level. The analysis reveals that the evolution of URT networking does not exhibit the characteristics of adverse effects diffusion, as highlighted in some previous studies. Instead, our findings provide a complementary perspective, emphasizing the role of decentralization and enhanced local connectivity in improving network resilience. These findings have immediate positive implications for Beijing URT and other evolving networks worldwide.