A statistical process control approach using cumulative sum control chart analysis for traffic data quality verification and sensor calibration for weigh-in-motion systems

ABSTRACT Weigh-in-motion systems have been widely used by state agencies to collect the traffic data on major state roadways and bridges to support traffic load forecasting, pavement design and analysis, infrastructure investment decision making, and transportation planning. However, the weigh-in-motion system itself poses difficulties in obtaining accurate data due to sensor characteristics that can be sensitive to vehicle speed, weather conditions, and changes in surrounding pavement conditions. This study focuses on developing a systematic methodology to detect weigh-in-motion sensor bias and enhance current practices for weigh-in-motion calibration. A mixture modeling technique using an expectation maximization algorithm was developed to divide the vehicle class 9 gross vehicle weight into three normally distributed components: unloaded, partially loaded, and fully loaded trucks. Then the well-known statistical process control technique cumulative sum control chart analysis was applied to expectation maximization estimates of daily mean gross vehicle weight for fully loaded trucks to identify and estimate shifts in the weigh-in-motion sensor. Special attention was given to the presence of autocorrelation in the data by fitting an autoregressive time-series model and then performing cumulative sum control chart analysis on the fitted residuals. Results from the analysis suggest that the proposed methodology is able to estimate a shift in the weigh-in-motion sensor accurately and also indicate the time point when the system went out of calibration. This methodology can be effectively implemented by state agencies, resulting in more accurate and reliable weigh-in-motion data.

[1]  Christopher M. Monsere,et al.  Bayesian Models for Reidentification of Trucks Over Long Distances on the Basis of Axle Measurement Data , 2011, J. Intell. Transp. Syst..

[2]  A R Forrest,et al.  Quality control. , 1978, British medical journal.

[3]  Mecit Cetin,et al.  Numerical Characterization of Gross Vehicle Weight Distributions from Weigh-in-Motion Data , 2007 .

[4]  Curtis Dahlin.  PROPOSED METHOD FOR CALIBRATING WEIGH-IN-MOTION SYSTEMS AND FOR MONITORING THAT CALIBRATION OVER TIME , 1992 .

[5]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[6]  P. L. Goldsmith,et al.  Cumulative Sum Tests: Theory and Practice , 1969 .

[7]  G. Box,et al.  Cumulative Sum Tests: Theory and Practice , 1968 .

[8]  Mecit Cetin,et al.  Bayesian Models for Re-identification of Trucks over Long Distances Based on Axle Measurement Data , 2009 .

[9]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[10]  Douglas C. Montgomery,et al.  Some Statistical Process Control Methods for Autocorrelated Data , 1991 .

[11]  A. T. Papagiannakis.  High Speed Weigh-in-Motion Calibration Practices , 2010 .

[12]  Christopher Higgins,et al.  Development of truck axle spectra from Oregon weigh-in-motion data for use in pavement design and analysis. , 2008 .

[13]  Marion R. Reynolds,et al.  EWMA and CUSUM control charts in the presence of correlation , 1997 .

[14]  A. T. Papagiannakis,et al.  Weigh-in-Motion Data Quality Assurance Based on 3-S2 Steering Axle Load Analysis , 1996 .

[15]  Elisabeth J. Umble,et al.  Cumulative Sum Charts and Charting for Quality Improvement , 2001, Technometrics.

[16]  Mecit Cetin,et al.  Short-Term Traffic Flow Prediction with Regime Switching Models , 2006 .

[17]  Edward T. Harrigan,et al.  NAtioNAl CooperAtive HigHwAy reseArCH progrAm , 2013 .

[18]  B McCall,et al.  STATES' SUCCESSFUL PRACTICES WEIGH-IN-MOTION HANDBOOK , 1997 .

[19]  Michel Ghosn,et al.  Collecting and using Weigh-in-Motion data in LRFD bridge design , 2009 .

[20]  E. S. Page.  CONTINUOUS INSPECTION SCHEMES , 1954 .

[21]  Indrajit Chatterjee,et al.  Implementation of Traffic Data Quality Verification for WIMSites , 2015 .

[22]  Marion R. Reynolds,et al.  Cusum Charts for Monitoring an Autocorrelated Process , 2001 .

[23]  Chih-Sheng Chou,et al.  Reidentification of Trucks on Basis of Axle-Spacing Measurements to Facilitate Analysis of Weigh-in-Motion Accuracy , 2014 .

[24]  Darcy M. Bullock,et al.  Quality Control Procedures for Weigh-in-Motion Data , 2004 .

[25]  Andrew Harvey,et al.  An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive–Moving Average Models by Means of Kaiman Filtering , 1980 .

[26]  T. Harris,et al.  Statistical process control procedures for correlated observations , 1991 .

[27]  D. Hawkins.  Self‐Starting Cusum Charts for Location and Scale , 1987 .

[28]  Michael M Marti,et al.  QUALITY CONTROL OF WEIGH-IN-MOTION SYSTEMS USING STATISTICAL PROCESS CONTROL , 1995 .