Development of a Practical Procedure for Data-Driven Weigh-in-Motion Equipment Calibration Scheduling to Assure Data Accuracy and Consistency over Time

Abstract

Weigh-in-motion (WIM) technology is a traffic monitoring technology that highway agencies use to obtain information about the weight, axle loading, and configuration of heavy vehicles moving at operational speed. To ensure high-quality WIM data, the Federal Highway Administration (FHWA) recommends regular calibration of WIM equipment. This study addresses the need to optimize the allocation of the limited resources that agencies have for WIM equipment calibration by developing a procedure for data-driven calibration scheduling. This was accomplished through an analysis of WIM measurement errors from test truck data collected during field performance validation and calibration events and an analysis of monthly changes in truck weight and axle loading characteristics, based on WIM data collected between calibration events. The analysis results were used to draw conclusions on the functional performance of different WIM sites. The study also demonstrates how the newly developed National Cooperative Highway Research Program (NCHRP) WIM Data Quality Assurance Analysis Tool can be used to compute truck weight and axle loading parameters and visualize data analysis results using four case studies: two WIM sites with piezo quartz sensors in asphalt pavements and two WIM sites with bending plate sensors in concrete pavements. This paper provides a practical procedure and recommendations that highway agencies can use to develop data-driven WIM calibration schedules that will ensure consistent high-quality WIM data for sites managed by an agency with the aid of the NCHRP WIM Data Quality Assurance Analysis Tool.