Towards resilient and smart urban road networks: Connectivity restoration via community structure

Abstract

In the time of global warming, smart and resilient cities need to have the ability to give quick responses to today’s frequent natural disasters. Building a resilient urban transportation system that can timely recover the accessibility of the rescue facilities is vital to the survival chances of citizens. From the perspective of selectively road restoration, we proposed a mixed integer programming model that is based on community hierarchy to provide quick disaster response for damaged urban road networks. This model can efficiently find roads that should give repairing priority to maximize the connectivity in a limited repairing scale. Network community structure has been innovatively introduced into our model, which can remarkably simplify the searching process by extracting critical connectivity information. The model has been tested on square-shaped road networks and Istanbul road networks. The results show that our community structure model gives superior solutions in significantly reduced computational time, and is practical in solving complex real-world large-scale connectivity repairing problems. These findings provide new insights into the understanding of the important role played by mesoscopic topological knowledge of road networks when seeking strategies and solutions for connectivity emergency restoration, which is significant for the development of resilient and sustainable cities. • We propose a community-based MIP approach for connectivity restoration. • The restoration strategies take the advantage of the mesoscopic structure. • The community structure markedly facilitates the optimization process. • The developed algorithms operate on large-scale urban road networks.