A Knowledge-Based Autonomous Vehicle System for Emergency Management Support

Abstract

The Federal Emergency Management Agency (FEMA) is tasked with allocating resources in responding to natural (e.g., earthquakes, volcanos, floods) and man-made (nuclear accidents, fires, hazardous waste) disasters. Data collection during these events must be performed in a timely manner to support the real-time decision support structure employed by FEMA. This paper describes an knowledge-based system for the command and control of multiple unmanned autonomous vehicles (UAV) performing surveillance in support of a viable emergency management decision-making system. The goal of the Emergency Management Expert Response thru Goal-driven Entities (EMERGE) is to assist a FEMA UAV operator by monitoring the status of individual UAVs and alerting FEMA personnel to existing or potential trouble areas. A knowledge-based system developed to assist human operators in the control of multiple air vehicles, EMERGE monitors the status of individual UAVs, alerting the EMERGE operator to existing or potential trouble areas. Assisting the operator by focusing his attention on tasks requiring resolution rather than system monitoring activities, EMERGE provides a mechanism by which multiple aerial vehicle surveillance can successfully support data collection and disaster response efforts.