Abstract
As modern societies become increasingly dependent on infrastructure systems, ensuring their functionality is paramount. Current simulation-based approaches for evaluating infrastructure wellbeing and resilience are known to be complex and time-consuming, making them unfeasible for practical applications. Indicators-based methods have been proposed as a promising alternative to simulations. However, a comprehensive set of indicators that cover all aspects of infrastructure systems has yet to be established. In this study, we performed an extensive literature review on wellbeing and resilience indicators specific to the transport infrastructure system. We filtered out duplications among the indicators and categorized them under distinct components and dimensions. These indicators can be tailored to fit specific circumstances and employed for/alongside advanced techniques such as Machine Learning, Bayesian Networks, and Fuzzy Logic. Acquiring a comprehensive set of wellbeing and resilience indicators can significantly improve stakeholder communication, empower communities in decision-making processes and adaptive management, and support resilience-strengthening strategies.
| Original language | English |
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| Number of pages | 8 |
| Publication status | Published - 2023 |
| Event | 14th International Conference on Applications of Statistics and Probability in Civil Engineering 2023 - Trinity College Dublin, Dublin, Ireland Duration: 9 Jul 2023 → 13 Jul 2023 https://icasp14.com/ |
Conference
| Conference | 14th International Conference on Applications of Statistics and Probability in Civil Engineering 2023 |
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| Abbreviated title | ICASP14 |
| Country/Territory | Ireland |
| City | Dublin |
| Period | 9/07/23 → 13/07/23 |
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