Identification of critical links within complex road networks using centrality principles on weighted graphs
Building resilient infrastructure has become a necessity in modern times. If a system can efficiently deal with failures, it is considered resilient. Roadways are some of the most vital infrastructures in the world. Their collapse due to unprecedented calamities would disrupt the normal functioning of society and cause significant financial loss. To minimize traffic jams and keep traffic flowing during such times, it is essential to identify important roads within a network and plan alternate routes to divert traffic. This study aims to find critical links in a road network and study their relationships with important nodes in the same network. It also highlights some traditional approaches and applies graph-theory concepts to measure node and edge importance within a network. An approach based on variable centrality is proposed. We have implemented our proposed system and evaluated its performance on multiple networks including a large scale statewide road network in Texas. Our preliminary experiments show promising results.
Bidikar, Nirupam; Zhang, Yunpeng; and Qiao, Fengxiang, "Identification of critical links within complex road networks using centrality principles on weighted graphs" (2021). Faculty Publications. 37.