TRANSIMS Evacuation Modeling
BackgroundBecause of the need for strengthened security measures and the availability of new methodologies for emergency scenario modeling, TRACC researchers and the Illinois Terrorism Task Force (ITTF) are using a TRANSIMS model of the Chicago metropolitan area to simulate the progress and impact of emergency evacuations in the Chicago Business District. This work is closely coordinated with the Chicago Metropolitan Agency for Planning (CMAP), the Illinois Department of Transportation (IDOT), the U.S. Department of Transportation (USDOT), the Chicago Office for Emergency Management and Communications (OEMC), the Region 5 Federal Emergency Management Agency (FEMA), and other organizations.
TRANSIMS is a particularly promising modeling tool for this application because of its unique capability to cover large metropolitan areas (and therefore far-reaching effects) while microsimulating on a second-by-second basis the escape movements of all individuals. Although the individuals in TRANSIMS comprise a "synthetic" population (based on extrapolations of census data), their whereabouts at any time of the day is well known, and behavioral models can be incorporated as needed. However, such a TRANSIMS model is particularly difficult to build because of the extensive need for detailed data and the associated computing time.
TRACC Research ActivitiesTRACC researchers are coordinating the activities surrounding the evacuation modeling project and building the model's major components using TRACC's high-performance computing cluster. A large number of Northern Illinois University (NIU) students are working on several tasks, including data acquisition and verification, under CMAP's direction.
Special methodologies are being developed to modify TRANSIMS' normal traffic forecasting features so they may be applied to the more dynamic evacuation scenarios. This includes the means to dynamically close streets, change routes and trips of displaced travelers and emergency responders, validate the base cases against available models and data, and visualize the modeling results so they are meaningful to the researchers.