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. Moreover, we describe the optimizations we applied to the JGraphT library to support multi-core computation. In this way, it is possible to perform road network analysis of large graphs (e.g., 53743 nodes and 125250 edges for the considered case study), representing real case studies, with relevant time savings (up to -87% on the adopted configuration).
Improving the Performance of Road Network Analysis: The Morandi Bridge Case Study
Leotta, Maurizio;Ribaudo, Marina
2019-01-01
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. Moreover, we describe the optimizations we applied to the JGraphT library to support multi-core computation. In this way, it is possible to perform road network analysis of large graphs (e.g., 53743 nodes and 125250 edges for the considered case study), representing real case studies, with relevant time savings (up to -87% on the adopted configuration).
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