In recent years, the analysis of the community response in case of disastrous events has become a research topic of paramount relevance due to the increasing number of calamities like flooding, hurricanes, and earthquakes. In particular, the possibility to use computer simulations to model and study the behaviour of thousands of people during an emergency evacuation can pro-vide valuable information to support many processes involved in emergency management. To this end, this work presents IdealCity, a hybrid model for evacuation simulation that couples the representation of the built environment and the transportation network with an agent-based simulation of the urban population. IdealCity can estimate the buildings’ damages and debris generated by a seismic event along with their effects on the other model layers (the agents and the roads). Besides that, the simulation takes into consideration as well the emergency response system by modelling shelters, hospitals, and ambulances (each of which has a specific behaviour within the environment). The model has been implemented and tested in a challenging test-bed that considers about 900,000 individuals, four different seismic scenarios, and three different times of the day. Results show that IdealCity can be used not only for predicting the population response but also for allowing decision-makers to estimate and intervene on critical response parameters, thus improving the inherent community resilience.

IdealCity: a Hybrid Approach to Seismic Evacuation Modeling / Battegazzorre, Edoardo; Bottino, Andrea; Domaneschi, Marco; Cimellaro, Gian Paolo. - In: ADVANCES IN ENGINEERING SOFTWARE. - ISSN 0965-9978. - ELETTRONICO. - 153:102956(2021). [10.1016/j.advengsoft.2020.102956]

IdealCity: a Hybrid Approach to Seismic Evacuation Modeling

Battegazzorre,Edoardo;Bottino,Andrea;Domaneschi,Marco;Cimellaro,Gian Paolo
2021

Abstract

In recent years, the analysis of the community response in case of disastrous events has become a research topic of paramount relevance due to the increasing number of calamities like flooding, hurricanes, and earthquakes. In particular, the possibility to use computer simulations to model and study the behaviour of thousands of people during an emergency evacuation can pro-vide valuable information to support many processes involved in emergency management. To this end, this work presents IdealCity, a hybrid model for evacuation simulation that couples the representation of the built environment and the transportation network with an agent-based simulation of the urban population. IdealCity can estimate the buildings’ damages and debris generated by a seismic event along with their effects on the other model layers (the agents and the roads). Besides that, the simulation takes into consideration as well the emergency response system by modelling shelters, hospitals, and ambulances (each of which has a specific behaviour within the environment). The model has been implemented and tested in a challenging test-bed that considers about 900,000 individuals, four different seismic scenarios, and three different times of the day. Results show that IdealCity can be used not only for predicting the population response but also for allowing decision-makers to estimate and intervene on critical response parameters, thus improving the inherent community resilience.
File in questo prodotto:
File Dimensione Formato  
IdealCity a Hybrid Approach to Seismic Evacuation Modeling.pdf

Open Access dal 03/01/2023

Descrizione: Articolo Principale
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: Creative commons
Dimensione 3.21 MB
Formato Adobe PDF
3.21 MB Adobe PDF Visualizza/Apri
1-s2.0-S0965997820310024-main.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 4.7 MB
Formato Adobe PDF
4.7 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2857924