Abstract

Infrastructure plays a key role in society. Recent collapses of bridges have underlined their importance for road functionality, causing disruptions to commuters and emergency vehicles. Major issues arise on rural roads, where the lack of redundancy leads to the isolation of entire communities. Actual approaches to assess the resilience of countryside roads rely on the availability of specific datasets, limiting their practical application; this issue is typically related to traffic data. This research aims to propose innovative algorithms to assess the road network’s vulnerability in rural areas, including a novel traffic data collection process and its calibration. The aggregate metric is called Detour-Impact Index (DII) and compares user costs before and after a disruptive event. The method uses traditional network-impact metrics in combination with a new algorithm that allows us to gather quantitative traffic data starting from qualitative information. User travel time showed good agreement between the proposed procedure and traditional web-based methods. Furthermore, the paper provides user delay costs functions accounting for traffic composition, trip purposes, vehicle operative costs, nonlinear volume–capacity relation, and average daily traffic. A significant aspect is the adaptability of this framework, as it is designed to be coupled with existing approaches. The method is demonstrated on a case study in Tuscany (Italy).

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