Weigh-in-Motion Data Analysis Software for Developing Traffic Data for Mechanistic Empirical Pavement Design
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:71732", author = "M. A. Hasan and M. R. Islam and R. A. Tarefder", title = "Weigh-in-Motion Data Analysis Software for Developing Traffic Data for Mechanistic Empirical Pavement Design", 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.", volume = "9", number = "12", pages = "2499-5", }