@article{10902/27315,
year = {2022},
month = {8},
url = {https://hdl.handle.net/10902/27315},
abstract = {Predicting and understanding mass evacuations are important factors in disaster management and response. Current modelling approaches are useful for planning but lack of real-time capabilities to help informed decisions as the disaster event evolves. To address this challenge, a real-time Evacuation Management System (EMS) is proposed here, following a stochastic approach and combining classical models of low complexity but high reliability. The EMS computes optimal assembly points and shelters and the related network of evacuation routes using GIS-based traffic, pedestrian and routing models including damaged assets or impassable areas. To test the proper operation performances of the EMS, we conducted a case study for the Gran Canaria wildfire},
organization = {This research and APC was funded by the European Union’s H2020 research and innovation programme under grant agreement No. 832576 (ASSISTANCE project).},
publisher = {MDPI},
publisher = {Applied Sciences, 2022, 12(15), 7876},
title = {Evacuation management system for major disasters},
author = {González Villa, Javier and Cuesta Jiménez, Arturo and Alvear Portilla, Manuel Daniel and Balboa Marras, Adriana},
}