Contraflow on major evacuation routes is one approach that has been adopted in many Gulf and eastern coastal states for hurricane evacuation. The idea is to reverse one direction of the roadway in order to accommodate the often substantially increased travel demand moving away from the impact area. Efficient planning and operation is critical to a successful contraflow implementation. One problem faced by the Alabama Department of Transportation is the scheduling of the different phases of this staged process. The timing for the deployment of equipment and personnel, and the initiation and termination of actual contraflow affects the effectiveness, safety and cost of the operation. For this research project, the University of Alabama researchers were tasked with the design of a decision support system for contraflow evacuation planning. Decision support systems are software systems that utilize sophisticated algorithmic approaches to solve problems. Selection of a suitable evacuation demand model was requisite to support the needs of the Alabama Department of Transportation Maintenance Bureau regarding contraflow pre-planning, and evaluating possible responses to a hurricane event. Beyond the adequacy of the demand model itself, the necessary supporting data must also be available. This paper focuses on the design of the demand forecasting module of the planned decision support system.