Statistical Validation for Short Count Traffic Counts Using Spatial Regression Model

The methodology to identify the traffic count stations that have anomalous counts was developed in this paper. Our proposed approach is to develop a spatial model that would separate out systematic and spatial variability in counts so that residual uncertainty may be identified. A principal component analysis was applied by using dimension reduction dealing with census data with many attributes. This proposed method would significantly improve the process of validating traffic counts by increasing the accuracy of reported counts and by reducing the time delay between data collection and reporting.