An agent-based model of short-notice tsunami evacuation in Waikiki, Hawaii
Karl Kim, Farnaz Kaviari, Pradip Pant, Eric Yamashita
Abstract
Evacuation planning is an essential part of transportation resilience. It is necessary to understand transportation systems and human behavior to plan for safe evacuation. This study estimates populations exposed to harm, clearance times and fatalities for short-notice evacuation for a catastrophic tsunami event. An Agent-Based Model (ABM) is developed and tested for Waikiki, Hawaii, with three travel modes: pedestrian, bicycle, and motor vehicles. The modeled environment includes the road network, tsunami inundation zones, and building footprints with vertical and horizontal evacuation destinations. Significant loss of life (38,760 persons) is estimated to occur with a catastrophic short-notice tsunami event. A new bridge over the Ala Wai Canal will create an additional exit route that could save 13,860 lives. Shortening tsunami detection and alert times by half would save 4,510 lives over the baseline, do-nothing scenario. Vertical evacuation is most effective and is estimated to save 55,770 lives. In addition to the importance to evacuation planning, the research using ABM supports longer term investment in transportation imnprovements, mitigation and adaptation.