Evacuation Planning: A Spatial Network Database Approach

Efficient tools are needed to identify routes and schedules to evacuate affected populations to safety in face of natural disasters or terrorist attacks. Challenges arise due to violation of key assumptions (e.g. stationary ranking of alternative routes, Wardrop equilibrium) behind popular shortest path algorithms (e.g. Dijkstra’s, A*) and microscopic traffic simulators (e.g. DYNASMART). Time-expanded graphs (TEG) based mathematical programming paradigm does not scale up to large urban scenarios due to excessive duplication of transportation network across time-points. We present a new approach, namely Capacity Constrained Route Planner (CCRP), advancing the idea of Time-Aggregated Graph (TAG) to provide Earliest-Arrival-Time given any Start-Time. Laboratory experiments and field use in Twin-cities for Homeland Security scenarios show that CCRP is more efficient than previous methods.