Analyzing road network robustness in major Chinese cities through hierarchical stroke-based representations

In this study, we explore the robustness of urban road networks, a crucial aspect of urban infrastructure whose failure can significantly disrupt urban functionality. Our approach offers a fresh perspective on network robustness by focusing on intrinsic street hierarchies within stroke-based representations across 20 major Chinese cities. These networks exhibit common complex properties, such as being scale-free and small-world. We determine street hierarchies based on the power law distribution of two key graph centrality measures: degree and betweenness. Our methodology involves a targeted attack strategy, sequentially removing roads from the highest to the lowest hierarchy in each urban street network. This process yields robustness profiles characterized by monotonic decreasing curves, which reflect changes in network connectivity and efficiency. The profiles not only provide valuable insights into urban structure and function, but also offer significant implications for practical road planning and urban resilience strategies.