This project assesses the feasibility of using statistically clustered property tax data instead of windshield survey data for input into the Internal Data Summary (IDS) trip generation model used by the North Carolina Department of Transportation. The report summarizes the clustering analysis and its data requirements. To gauge clustering resource requirements for a case study application, NCSU researchers examined the town of Pittsboro. Comparing the traffic flow outputs of the traditional modeling techniques and those resulting from the use of the clustering method to 56 ground count stations, the research finds that clustering and traditional methods yield similar results. The main benefit resulting from the use of the clustering technique is an 85% reduction in work-hours required to gather the input data. The major drawback is that advanced statistical training is required to implement the technique.
