| description abstract | Networked infrastructures serve as essential backbones of society. In particular, road transportation networks have a principal role in people’s everyday lives because they facilitate physical connectivity. External factors, such as disasters and failures, may degrade the performance of road networks. For example, severe flooding may disrupt a large area of a network, leading to cancellations and delay of several trips over the network. In addition, the collapse of a bridge could render certain nodes and links ineffective, thereby affecting traffic flow conditions. The authors formalized and developed a computational framework to assess vulnerability of road networks due to critical artificial or natural disruptions. The framework is built upon recent developments in interdisciplinary domains, such as network science, computational science, and transportation engineering. Using the proposed framework for the Greater Philadelphia road network, the network was divided into several high-critical, medium-critical, and low-critical clusters. The clustering results varied based on the time and severity of disruption. For instance, during the p.m. peak, disruption of roads within the city of Philadelphia was more critical than other roads of the region. However, during the a.m. peak, the roads surrounding the city of Philadelphia were more critical. The framework was validated using real-world observations and simulated traffic results. | |
