# Evacuation Management System for Major Disasters
## 5 Discussion & Conclusions  
Almost all regions, local governments, first responders and international organisations are prepared for the most common disasters through emergency response, response and resilience plans. In designing these plans, there are a multitude of tools and expert studies that allow the deployment of both temporary and permanent shelters, assembly points and evacuation and intervention strategies [37]. However, the problem arises when the disaster occurs, and the planning phase transitions to the response phase. At that point, the initial static plans are used as far as the actual situation allows, and that is where the intuition and experience of the first responders comes into play. Therefore, it is crucial that real-time decision-support systems can assist in these decisions, reducing workloads and stressful situations. However, these decision-support systems require a trade-off between performance and simulation times in the event of a disaster [38]. Figure 8: Simulation of evacuation processes for the four use cases. Each curve represents the total arrival time to the shelters of the different evacuees considering their entire evacuation process (pre-movement, pedestrian and vehicular movement times). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Evacuation** & **Evacuees** & \begin{tabular}{c} **Routes/Interaction** \\ **Road Sections** \\ \end{tabular} & **Simulation Time** \\ \hline \hline \begin{tabular}{c} Artenara \\ 10/08 \\ \end{tabular} & 800 & 6/14 & 2 min, 51 s \\ \hline \begin{tabular}{c} Artenara \\ 11/08 \\ \end{tabular} & 245 & 8/21 & 3 min, 51 s \\ \hline \hline \
\begin{tabular}{c} Santa Maria de Guia \\ 17/08 \\ \end{tabular} & 100 & 2/4 & 0 min, 4 s \\ \hline \hline
\begin{tabular}{c} Agaete \\ 18/08 \\ \end{tabular} & 1000 & 4/11 & 0 min, 9 s \\ \hline \hline \end{tabular}
\end{table} 
Table 3: System performance analysis running on an eight-core laptop. Hence, in this paper an Evacuation Management System was presented and tested with a use case. Related to this purpose, the exploration and understanding of major disasters was carried out to develop models according to the evolution of the disasters. The proposed system integrates different traditional, well-known models to address a full evacuation strategy based on a mixed evacuation approach, thereby reducing the computational load by applying a stochastic methodology that is able to operate in real time. The system was applied to a particular case study (Gran Canaria wildfire) involving multiple simultaneous evacuations and a main damaged area. This case study was used to verify the proper operation of the system, testing all the individual models. The presented system is significant in at least three major respects. First, the system is supported by ultrafast evacuation calculations and real-time decision support to provide optimal evacuation strategies, in contrast to the models designed for planning [17; 39] that require a greater computational load. Second, the system allows comprehensive planning of mass evacuations, including evacuation routes that avoid damaged assets, optimal locations of shelters and assembly points, and relevant decision-making information related to intervention times. This approach departs from the traditional thought where pedestrian evacuation, sheltering strategies or vehicle modelling of unusual or critical situations is analysed in isolation [40]. Third, the underlying models that are used by the system were validated both within this development through the use case and previously by other studies as seen in the introduction, thus giving an acceptable credibility to the results provided by the tool. Nevertheless, readers should keep in mind the practical limitations of the proposed system. This system is limited by the selected evacuation strategy, as the hypothesis does not allow the provision of only vehicular or pedestrian evacuations.