Background/Objectives

Climate change induced disasters such as the Syrian, Australian Maui and California wildfires are displacing people within their own countries.

The tools and procedures used to deal with this increasingly common situation are reactive, post-event. This leads to responses which can be inefficient and affect both migrating and receiving communities unfairly. The bulk of climate change impacts that lead to evacuations are borne by communities that are the least able to adapt. Planning for evacuation before the need is critical in preparing communities and in lowering the cost of and increasing the probability of an adequate response.

A robust simulation tool assists in planning for evacuations. This can aid the planner in modeling the flow of community members, supporting the routes, selection of receiving communities and pre stocking of resources. Policy variations can be applied to the model for evaluation.

Approach/Activities

This is a laboratory project using existing geographic mapping, traffic and routing technology. The scale of the simulation is determined by emergency services. Geographic and infrastructure data are integrated as needed for the selected area of interest. Emergency services denote the starting point of the evacuation and its possible destinations. The model integrates the area information and plans routes and identifies possible negative impacts. To test other scenarios, emergency services create a policy to define the created scenario. The base technologies investigated for the model implementation are GIS and other routing / geographic technologies. Custom routing algorithms use the base utilities but enhance them as needed to represent detrimental conditions in an evacuation such as traffic blockages, flooded routes. AI techniques and parallel processing tools are used to minimize the time to reach a solution by the model and to suggest policy approaches.

Results/Lessons Learned

Emergency services implement simulation designs to test and author evacuation response plans. Execution of the model is done using custom algorithms and base technology which is used by the custom algorithms. The custom algorithms describe transportation impacts based on access (flooding, traffic blockages) policy (evacuation routing to areas that have more gas stations, highways with traffic lanes running in one direction) and services (hospitals, food access). The base technology supports generic access to geographic information and routing information for a geographic area.