Abstract
Road network analysis is a fundamental tool for city planners and engineers for preventing, or finding possible solutions to, gridlock congestion and immobility. In this work, we describe the computation of some classical centrality measures for the road network of the region Liguria, in particular focusing on the effects of the 2018 Morandi bridge collapse. Given the size of the network graph derived from the OpenStreetMap publicly-available data, we extended the JGraphT library to support multi-core computation. In this way, it is possible to deal with large graphs (e.g., 53743 nodes and 125250 edges for the considered case study), representing real networks, with relevant time savings (up to -87% on the adopted configuration). Results show that, on the considered case study, even a classical measure like Betweenness centrality is able to provide interesting insights on the road network under investigation.
Published Version
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