Weigh-in-Motion Data Analysis Software for Developing Traffic Data for Mechanistic Empirical Pavement Design
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Weigh-in-Motion Data Analysis Software for Developing Traffic Data for Mechanistic Empirical Pavement Design

Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

Abstract:

Currently, there are few user friendly Weigh-in- Motion (WIM) data analysis softwares available which can produce traffic input data for the recently developed AASHTOWare pavement Mechanistic-Empirical (ME) design software. However, these softwares have only rudimentary Quality Control (QC) processes. Therefore, they cannot properly deal with erroneous WIM data. As the pavement performance is highly sensible to the quality of WIM data, it is highly recommended to use more refined QC process on raw WIM data to get a good result. This study develops a userfriendly software, which can produce traffic input for the ME design software. This software takes the raw data (Class and Weight data) collected from the WIM station and processes it with a sophisticated QC procedure. Traffic data such as traffic volume, traffic distribution, axle load spectra, etc. can be obtained from this software; which can directly be used in the ME design software.

Keywords: Weigh-in-motion, software, axle load spectra, traffic distribution, AASHTOWare.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1110726

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References:


[1] Tarefder, R. A., and M. R. Islam. “Study and Evaluation of Materials Response in Hot Mix Asphalt Based on Field Instrumentation”. Final Report, Project ID. NM11MSC-03, 2015, Research Bureau, New Mexico Department of Transportation (NMDOT), pp. 1–195, 2015.
[2] FHWA. “Traffic Monitoring Guide”. Federal Highway Admin., U. S. Department of Transportation., 2013, Washington, D. C.
[3] Hasan, M. A., M. R. Islam and R. A. Tarefder. “Site Specific versus Pavement Mechanistic Empirical Default Traffic Data on Interstate Pavement Performance”. Accepted, 95th Annual Meeting of the Transportation Research Board, Transportation Research Board, 2016, Washington, D.C.
[4] Tarefder, R. and J. I. Rodriguez-Ruiz. WIM Data Quality and its Influence on Predicted Pavement Performance. Transportation Letters: The International Journal of Transportation Research, 5(3), 2013, pp. 154-163.
[5] Wilkinson, J. Chaparral Systems Corp. “TrafLoad User’s Manual”. NCHRP Report 538, Part 3, 2005, Washington, DC.
[6] Quinley, R., 2010. WIM Data Analyst’s Manual. Report No. FHWA-IF- 09-038, Washington, DC.
[7] Ramachandran, A. N., Taylor, K. L., Stone, J. R., and Sajjadi, S. S. “NCDOT Quality Control Methods for Weigh in Motion Data”. Public Works Management Policy 2011, Volume No. 16, DOI: 10.1177/1087724X10383583, pp. 3-19, 2011, SAGE Publications.
[8] Mia, D., Turochy, R. E. and Timm, D. H. “Quality control of weigh-inmotion data incorporating threshold values and rational procedures.” Transportation Research Part C Emerging Technologies. 11/2013; 36:116–124. DOI: 10.1016/j.trc.2013.08.012.