EventsThe 1st International Online Conference on CivilEng
Published
This submission belongs to the session S1. Mathematical Models for Civil Engineering of the event The 1st International Online Conference on CivilEng
Published date
09 Nov, 2026
Academic Editor
author-avatarAngelo Luongo
Citation
Irina Di Ruocco, A Composite Vulnerability and Resilience Index for European High-Speed Rail Infrastructure, in Proceedings of The 1st International Online Conference on CivilEng, 12 November–13 November 2026, MDPI: Basel, Switzerland
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A Composite Vulnerability and Resilience Index for European High-Speed Rail Infrastructure

1. Department of Economics, Mathematics and Statistics, University of Trieste, Via A. Valerio 4/1, 34127 Trieste, Italy
Abstract

High-speed rail infrastructures are strategic civil engineering systems whose reliability, safety and continuity depend on the interaction between physical asset conditions, operational pressure, maintenance capacity, environmental exposure and network criticality. Across Europe, countries such as Italy, Germany, Spain and France have developed extensive high-speed rail networks, but they are increasingly exposed to multiple sources of vulnerability, including ageing infrastructure, traffic congestion, extreme weather events, service disruptions and growing maintenance needs. Although recent studies have advanced predictive maintenance and data-driven diagnostics in railway engineering, many approaches rely on detailed sensor-based or track-condition datasets that are not consistently available across countries. This limits the development of comparable assessments of infrastructure vulnerability and resilience at European scale.

This study proposes a mathematical framework for constructing a composite Vulnerability and Resilience Index for high-speed rail infrastructure. The analysis focuses on selected European corridors in Italy, Germany, Spain and France and combines publicly available indicators from European and national sources, including infrastructure characteristics, traffic intensity, punctuality and disruption records, safety indicators, maintenance and investment proxies, and climate-related stressors. The methodology is structured in four steps. First, indicators are organised into five analytical dimensions: infrastructure exposure, operational stress, safety and reliability, climate sensitivity, and adaptive/maintenance capacity. Second, variables are normalised to enable cross-country comparison. Third, entropy-based weighting and sensitivity analysis are used to construct a Vulnerability Index and a complementary Resilience Index. Fourth, the resulting indices are used to rank corridors and identify the main drivers of infrastructure vulnerability and resilience.

The innovation of the contribution lies in translating fragmented and heterogeneous public railway data into a transparent, replicable and mathematically structured assessment tool.

The expected results include a comparative diagnostic matrix for European high-speed rail corridors and a ranking of infrastructure systems according to their vulnerability and resilience levels. The proposed framework can support infrastructure managers and policymakers in identifying priority corridors, improving maintenance planning and strengthening the resilience of high-speed rail systems under increasing operational and climate-related pressures.

Keywords
High-Speed Rail
Vulnerability Index
Resilience Index
Civil Engineering
Composite Indicators
Railway Infrastructure
Maintenance Capacity
Climate Risk
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