VULNERABILITY ANALYSIS OF ROAD TRAFFIC NETWORKS IN CASE OF SIMULATED EXTREME EVENTS

In contemporary societies, critical infrastructure systems, including road transportation networks, play a key role in ensuring the mobility of people and goods. The recent increase in extreme and unpredictable events, such as those caused by climate change, underlines the need for strategies to strengthen the resilience of transportation road networks against disruption events. This thesis discusses vulnerability analysis of road traffic networks in simulated extreme events (floods), focusing on the use of open data and open-source software tools. The study aims to evaluate the resilience of road networks by proposing two methodologies: GIS-based spatial and topological vulnerability analysis, and vulnerability analysis with mesoscopic simulation of traffic demand to quantify road network traffic performance and functionality. These methodologies were applied to two case studies in Northern Italy: The Metropolitan City of Turin and the Province of Alessandria. For application of both methodologies, Initially, the study area is defined, and traffic zones and centroids are established to represent trip origins and destinations. The road network is modeled as a graph model including nodes and links, weighted by parameters such as travel time and distance. This model undergoes a series of analyses to determine its performance under baseline and disruption scenarios. In the spatial and topological analysis, key characteristics such as connectivity, travel distances, and travel times are evaluated to understand the network's efficiency and structure. The scenarios developed for disruption events include simulated flood events, assessing their impact on the road network's functionality. The second methodology, vulnerability analysis with traffic demand assignment integrates traffic demand data into the road network model to simulate traffic demand and its response to disruptions. By integrating traffic demand, including internal, external, and crossing trips, the analysis provides an understanding of how disruptions affect not just the physical infrastructure but also the operational aspects of the road network. Finaly, Serviceability-based methods, including route comparison and O/D skim matrix comparison, and accessibility-based methods, are used to evaluate road network performance. The findings highlight vulnerabilities in the road networks of the Metropolitan City of Turin and the province of Alessandria, providing insights into areas that require improvements to enhance overall network resilience. By combining spatial, topological, and traffic demand data, the thesis offers a framework for assessing the resilience of road networks. These insights are helpful for planners and policymakers to mitigate the impacts of extreme events on road transportation infrastructures.