In transportation analysis and planning, road network vulnerability analysis is a significant field of research, since it can help authorities to identify critical infrastructures and to recommend budget allocations. Disruptive events cause damages in structural and infrastructural components, inducing drastic changes in travel demand. However, this issue has received limited attention in past studies, which generally assumed that travel demand remains fixed. Furthermore, because of the availability of limited economic resources, authorities need to select a limited number of facilities to be retrofitted. The aim of this paper is to identify the best retrofitting strategy for bridges after an earthquake, considering travel demand changes few days after the event. The multi-disciplinary framework adopted in this paper evaluated damages on bridges and buildings according to earthquake attributes. Variations in network and land use characteristics, relocation of households and fatalities were simulated. Different retrofitting strategies for bridges were selected subject to a budget constraint, generating the corresponding network scenarios. Changes in travel demand after the earthquake were estimated for each scenario by applying an Activity-Based Model, which simulated users’ daily activity pattern. Specific vulnerability indicators were calculated to identify the best retrofitting scenario, i.e. the scenario producing the lowest travel demand changes. The procedure was applied to the road network of Conegliano, a town in northern Italy. Results show that the model realistically reproduced adjustment in users’ activities, and that ignoring travel demand changes or considering each indicator as independent leads to miss the identification of the best retrofitting strategy.
Road network vulnerability assessment. Post-quake travel demand modelling and accessibility variation / Ceccato, Riccardo; Gastaldi, Massimiliano; Gecchele, Gregorio; Diana, Marco; Zanini, Mariano Angelo; Rossi, Riccardo; Pellegrino, Carlo. - ELETTRONICO. - (2017). (Intervento presentato al convegno Transportation Research Board 96th Annual Meeting tenutosi a Washington D.C. nel 8/1/2017-12/1/2017).
Road network vulnerability assessment. Post-quake travel demand modelling and accessibility variation
CECCATO, RICCARDO;Diana, Marco;
2017
Abstract
In transportation analysis and planning, road network vulnerability analysis is a significant field of research, since it can help authorities to identify critical infrastructures and to recommend budget allocations. Disruptive events cause damages in structural and infrastructural components, inducing drastic changes in travel demand. However, this issue has received limited attention in past studies, which generally assumed that travel demand remains fixed. Furthermore, because of the availability of limited economic resources, authorities need to select a limited number of facilities to be retrofitted. The aim of this paper is to identify the best retrofitting strategy for bridges after an earthquake, considering travel demand changes few days after the event. The multi-disciplinary framework adopted in this paper evaluated damages on bridges and buildings according to earthquake attributes. Variations in network and land use characteristics, relocation of households and fatalities were simulated. Different retrofitting strategies for bridges were selected subject to a budget constraint, generating the corresponding network scenarios. Changes in travel demand after the earthquake were estimated for each scenario by applying an Activity-Based Model, which simulated users’ daily activity pattern. Specific vulnerability indicators were calculated to identify the best retrofitting scenario, i.e. the scenario producing the lowest travel demand changes. The procedure was applied to the road network of Conegliano, a town in northern Italy. Results show that the model realistically reproduced adjustment in users’ activities, and that ignoring travel demand changes or considering each indicator as independent leads to miss the identification of the best retrofitting strategy.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2709808
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