To ensure that transport infrastructure provides acceptable levels of service with respect to extreme events, the resilience of the infrastructure needs to be estimated and targets for it need to be set. Recent work in the European research project Future Proofing Strategies for Resilient Transport Networks against Extreme Events (Foresee) has shown how this can be done in situations with a wide range of available data, time frames for the estimation and expertise. This paper provides an example of how an infrastructure manager can use the guideline to estimate the resilience of, and set resilience targets for, an example transport system in a relatively short period of time, even in the case of limited expertise in all the relevant areas and limited knowledge and information on all the basic input variables. The example is fictive but realistic. It is based on a transport system consisting of a section of the A16 highway, in Italy, where a potential landslide could discharge enough material to damage road sections and bridges. The resilience is estimated using resilience indicators with differentiated weights, and the resilience targets are set using cost-benefit analysis, to identify the indicators to be improved first.

Estimating the resilience of, and targets for, a transport system using expert opinion

Martani, C;di Gennaro, F;
2021-01-01

Abstract

To ensure that transport infrastructure provides acceptable levels of service with respect to extreme events, the resilience of the infrastructure needs to be estimated and targets for it need to be set. Recent work in the European research project Future Proofing Strategies for Resilient Transport Networks against Extreme Events (Foresee) has shown how this can be done in situations with a wide range of available data, time frames for the estimation and expertise. This paper provides an example of how an infrastructure manager can use the guideline to estimate the resilience of, and set resilience targets for, an example transport system in a relatively short period of time, even in the case of limited expertise in all the relevant areas and limited knowledge and information on all the basic input variables. The example is fictive but realistic. It is based on a transport system consisting of a section of the A16 highway, in Italy, where a potential landslide could discharge enough material to damage road sections and bridges. The resilience is estimated using resilience indicators with differentiated weights, and the resilience targets are set using cost-benefit analysis, to identify the indicators to be improved first.
2021
hazards
risk & probability analysis
transport management
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1240659
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