Development of Procedure for Automated Segmentation of Pavement Rut Data

Abstract

To effectively manage pavements, it is necessary to know the current pavement condition. The Florida Department of Transportation uses an automated road profiler system to survey pavement condition. This system uses ultrasonic technology and is able to collect rut data at a high speed with tolerable accuracy. The system software processes the raw data into a density of 62 data points per kilometer. For pavement management applications, a summary of the rut data would be more useful than simply a list of them along the road. Thus, the objective of this study was to find a better way to reduce the amount of data and maintain the attributes as much as possible. To achieve the goal, an SAS (Statistical Analysis Software) segmentation program based on the cumulative difference approach (CDA) was developed to process the rut data. With this program a road may be divided into a number of segments within which the rut depth is relatively uniform. The average of the rut depths within this segment may represent the rut depth value of the whole segment. The data reduction rate and the sum of squared errors (SSE) were used in a case study as the indicators to compare the results from different user-specified constraints and to illustrate the usefulness of the CDA in rut data reduction. It may be concluded that the CDA is an effective method for rut data reduction in pavement management applications.