Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
Many state departments of transportation have been collecting various traffic data through the Automatic Traffic
Recorder (ATR) and Weigh-in-Motion (WIM) systems as outlined in the Traffic Monitoring Guide (TMG)
published by USDOT. A pooled fund study led by MnDOT was conducted in 2002 to determine traffic data editing
procedures. It is challenging to identify potential problems associated with the collected data and ensure data
quality. The WIM system itself presents difficulty in obtaining accurate data due to sensor characteristics, complex
vehicle dynamics, and the pavement changes surrounding the sensor over time. To overcome these limitations,
calibration procedures and other monitoring activities are essential to data reliability and accuracy. Current practice
of WIM calibration procedures varies from organization to organization. This project aims to understand the
characteristics of WIM measurements, identify different WIM operational modes, and develop mixture models for
each operation period. Several statistical data analysis methodologies were explored to detect measurement drifts
and support sensor calibration. A mixture modeling technique using Expectation Maximization (EM) algorithm and
cumulative sum (CUSUM) methodologies were explored for data quality assurance. An adjusting CUSUM
methodology was used to detect data anomaly. The results indicated that the adjusting CUSUM methodology was
able to detect the sensor drifts. The CUSUM curves can trigger a potential drifting alert to the WIM manager.
Further investigation was performed to compare the CUSUM deviation and the calibration adjustment. However,
the analysis results did not indicate any relationship between the computed CUSUM deviation and the calibration
Minnesota Traffic Observatory Laboratory, Department of Civil Engineering, University of Minnesota
Liao, Chen-Fu; Davis, Gary A..
Traffic Data Quality Verification and Sensor Calibration for Weigh-In-Motion (WIM) Systems.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
Retrieved from the University of Minnesota Digital Conservancy,
Content distributed via the University of Minnesota's Digital
Conservancy may be subject to additional license and use
restrictions applied by the depositor.