The increasing occurrence of extreme weather events poses significant challenges to urban road transport systems, as spatially diffused disruptions (e.g., flooding) can trigger congestion spillovers and network-wide performance losses. This study proposes a multi-scenario, demand-segmented framework to assess flood-induced transport vulnerability and applies it to the private road network of the Milan metropolitan area. Flood hazard maps are used in combination with a static traffic assignment model to simulate performance degradation under multiple flood scenarios. A composite link-level vulnerability indicator is introduced, combining local congestion effects with systemic relevance measures derived from network-wide travel time changes, and is applied across distinct demand segments. Results show that vulnerabilities concentrate along ring-road systems and their access corridors, with inter-ring and external trips experiencing the greatest impacts, while internal trips are mainly affected by localized congestion. The findings demonstrate that flood-induced transport vulnerability is strongly shaped by demand patterns, network structure and exposure to risk. The proposed framework supports policy-oriented identification of critical road links and targeted preparedness strategies, and it is transferable to other metropolitan areas with comparable urban forms and flood exposure.

Vulnerability assessment of urban road networks under extreme weather events

Guglielmi, Francesco;Mariano, Pietro;Coppola, Pierluigi
2026-01-01

Abstract

The increasing occurrence of extreme weather events poses significant challenges to urban road transport systems, as spatially diffused disruptions (e.g., flooding) can trigger congestion spillovers and network-wide performance losses. This study proposes a multi-scenario, demand-segmented framework to assess flood-induced transport vulnerability and applies it to the private road network of the Milan metropolitan area. Flood hazard maps are used in combination with a static traffic assignment model to simulate performance degradation under multiple flood scenarios. A composite link-level vulnerability indicator is introduced, combining local congestion effects with systemic relevance measures derived from network-wide travel time changes, and is applied across distinct demand segments. Results show that vulnerabilities concentrate along ring-road systems and their access corridors, with inter-ring and external trips experiencing the greatest impacts, while internal trips are mainly affected by localized congestion. The findings demonstrate that flood-induced transport vulnerability is strongly shaped by demand patterns, network structure and exposure to risk. The proposed framework supports policy-oriented identification of critical road links and targeted preparedness strategies, and it is transferable to other metropolitan areas with comparable urban forms and flood exposure.
2026
Flood risk, Multi-scenario analysis, Demand heterogeneity,Traffic assignment, Resilience
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1311458
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