Network criticality assessment aims to identify important nodes or links within a network that that are critical to its overall performance. Existing studies often focus on factors such as traffic volume and sociodemographic attributes, giving preference to heavily traveled highways in densely populated areas. Rural highways, particularly those with low traffic volumes, tend to be undervalued, despite their potential significance in sustaining network connectivity and facilitating access to services and opportunities within local communities. This paper addresses this concern by developing a criticality framework grounded in the egalitarian principle. The framework comprises two complimentary measures: normalized betweenness centrality and detour importance. The former measures a road’s relative importance in efficiently linking the local network by quantifying the percentage of origin-destination pairs within the neighborhood that utilize it. The latter, detour importance, reflects the aggregated percentage of trips rerouted to the road during disruptions to other critical roads, thereby highlighting its role in providing the needed redundancy of the network. Given the fundamental role of finding realistic shortest paths in this analysis, a large-scale GPS-based probe vehicle dataset is integrated to provide real-world travel time information. The results from the Kentucky case study validate the effectiveness of the developed framework. The framework utilizes efficient algorithms and readily available data, making it practically feasible for large-scale applications.

网络关键性评估旨在识别网络中对其整体性能至关重要的重要节点或链路。现有的研究通常关注交通量和社会人口特征等因素，优先考虑人口稠密地区的交通繁忙的高速公路。农村公路，特别是那些交通量较低的公路，尽管在维持网络连接和促进当地社区内的服务和机会方面具有潜在的重要意义，但其价值往往被低估。本文通过开发一个基于平等原则的关键性框架来解决这一问题。该框架包括两个补充指标：标准化介数中心性和绕行重要性。前者通过量化邻域内使用该道路的起点-目的地对的百分比来衡量道路在有效连接本地网络方面的相对重要性。后者，即绕行重要性，反映了在其他关键道路中断期间改道至该道路的出行总百分比，从而凸显了其在提供网络所需冗余方面的作用。鉴于在此分析中寻找实际最短路径的基本作用，集成了基于 GPS 的大规模探测车数据集以提供真实世界的行程时间信息。肯塔基州案例研究的结果验证了所开发框架的有效性。该框架利用高效的算法和现成的数据，使其对于大规模应用来说实际上是可行的。