Approach to Quantify the Impact of Disruptions on Traffic Conditions using Dynamic Weighted Resilience Metrics of Transport Networks

Abstract

Transport networks are essential for societies. Their proper operation has to be preserved to face any perturbation or disruption. It is therefore of paramount importance that the modeling and quantification of the resilience of such networks are addressed to ensure an acceptable level of service even in the presence of disruptions. The paper aims at characterizing network resilience through weighted degree centrality. To do so, a real dataset issued from probe vehicle data is used to weight the graph by the traffic load. In particular, a set of disrupted situations retrieved from the study dataset is analyzed to quantify the impact on network operations. Results demonstrate the ability of the proposed metrics to capture traffic dynamics as well as their utility for quantifying the resilience of the network. The proposed methodology combines different metrics from the complex networks theory (i.e., heterogeneity, density, and symmetry) computed on temporal and weighted graphs. Time-varying traffic conditions and disruptions are analyzed by providing relevant insights on the network states via three-dimensional maps.

A Geometric Classification of World Urban Road Networks

“…The nodes are the intersections formed by road segments and dead ends, and the links are the road segments themselves that connect the nodes. To quantitatively characterize the topological properties of road networks, various measures have been used in the literature, including network centrality measures such as betweenness centrality [13,27,34,37,51,52], closeness centrality [13,50,[53][54][55], degree centrality [13,45,[56][57][58][59] and clustering coefficient [35]. Each measure can be used to capture a certain property of the road networks.…”

“…For instance, interruptions to any road links causes a connectivity loss; however, the degree of damage to the network varies depending on the properties of the interrupted links. In addition, road network properties can be used to identify the vulnerabilities in the networks, and to plan or improve their resilience [25][26][27]. Furthermore, characterizing and studying road networks across different cities can provide insights to further our understanding of urbanization and transport planning [28].…”