Use of Data Mining in Emergency Evacuation Planning

Evacuating large numbers of people during a natural disaster or terrorist attack is a vital challenge for emergency management professionals. This is even a continuous pressure on the management in the hurricane zones. Hurricanes Katrina and Rita vividly illustrated this problem. Miles-long traffic jams on the highways during any evacuation in Louisiana and Texas expose the limitations of the regional transportation network and the inadequacy of evacuation route planning. A good plan should be designed to allow comprehensive evacuation planning studies including estimates of evacuation times, development of traffic management and control strategies, identification of evacuation routes, and traffic control points and other elements of an evacuation plan. Efficient tools are needed to produce plans that identify routes and schedules to evacuate affected populations as quickly and effectively as possible. Data mining is one of the most powerful tools in data analyzing, visualizing and forecasting which has been used in numerous applications both in private and public sectors. This paper makes an effort to survey and organize the current knowledge in the use of data mining methods and tools in emergency evacuation planning, as well as presents the challenges and future research directions. The findings come as a result of a thorough bibliography survey. The paper concludes by presenting future research directions.