Recommended Procedure to Adjust Inaccurate Weigh-in-Motion Data

Abstract

Weigh-in-motion (WIM) stations are used to monitor traffic volumes and loadings on roads and bridges. When a station is installed, a vehicle of known axle weights is typically used to calibrate the sensors. Because of environmental changes, pavement changes, sensor fatigue, and repeated loadings, the initial calibration doesn’t always maintain its validity. Therefore, the WIM station output must be monitored so that potential problems can be identified and corrected. It is common for analysts to discover that WIM data are inaccurate when they are attempting to use the data for design or planning. An analyst must then decide whether to conduct the analysis with inaccurate data or to not conduct the analysis at all. There is a need to develop a procedure that allows inaccurate WIM data to be adjusted and remain usable. Adjustment of WIM data after they have been collected may not be an acceptable practice to all agencies or for certain applications. A new accuracy metric was developed that relates Class 9 front axle weight with gross vehicle weight with data from the Long-Term Pavement Performance (LTPP) program. This new metric and other existing accuracy metrics in the literature will serve as baselines for adjusting the data. The adjustment procedure involves time series analysis, which eliminates temperature-induced variations in weight measurements that are known to occur with certain WIM sensors. The adjustment procedure is applied to an LTPP WIM station to illustrate the data before and after adjustment.