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Article Dans Une Revue Data in Brief Année : 2023

Measuring road network resilience by loss of serviceability index for critical road links

Résumé

In complex networks such as road infrastructure systems, disruptive events have direct consequences (loss of lives, structural damage, economic losses, etc.) related to the sub-system level directly affected, as well as indirect consequences on the overall system level, such as loss of functionality and related monetary consequences. To quantify the influence of component failures on network performance, complex network analysis makes it possible to represent the relation between its components and the consequences to estimate the functionality of the system. The serviceability of a road network is the possibility to use it during a given time period, and represents the performance of the system. Thus, time to restored serviceability after a disruptive event is a measure of road transportation resilience. In this paper, network analysis performed by the OSMnx Python package, supplied by road network data from OpenStreetMap, is applied to a Spanish motorway case study. The loss of serviceability index is obtained, combining the results of road links failure scenarios based on shortest paths and travel times to estimate road network resilience. The proposed methodology allows a suitable evaluation of the influence of road links in the risk assessment and management strategies by road infrastructure owners and managers.

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hal-04197365 , version 1 (06-09-2023)

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Marianna Loli, George Kefalas, Stavros Dafis, Stergios Aristoteles Mitoulis, Franziska Schmidt. Measuring road network resilience by loss of serviceability index for critical road links. Data in Brief, 2023, 48, ⟨10.1016/j.dib.2023.109062⟩. ⟨hal-04197365⟩
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