Measured versus Default Interstate Traffic Data in New Mexico, USA
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Measured versus Default Interstate Traffic Data in New Mexico, USA

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

Abstract:

This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, Traffic, Weigh-in-Motion, Axle load Distribution.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1110439

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References:


[1] Mechanistic-Empirical Pavement Design Guide, Interim Edition: A Manual of Practice. American Association of State Highway and Transportation Officials (AASHTO), Washington, D. C., 2008.
[2] 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.
[3] Timm, D. H., J. M. Bower, and R. E. Turochy. Effect of Load Spectra on Mechanistic–Empirical Flexible Pavement Design. In Transportation Research Record: Journal of the Transportation Research Board, No. 1947, Transportation Research Board of the National Academies, Washington, D.C., 2006, pp. 146–154.
[4] Tran, N. H., and K. D. Hall. Development and Influence of Statewide Axle Load Spectra on Flexible Pavement Performance. In Transportation Research Record: Journal of the Transportation Research Board, No. 2037, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 106–114.
[5] Tran, N. H., and K. D. Hall. Development and Significance of Statewide Volume Adjustment Factors in Mechanistic-Empirical Pavement Design Guide. In Transportation Research Record: Journal of the Transportation Research Board, No. 2037, Transportation Research Board of the National Academies, Washington, D.C., 2007, pp. 97–105.
[6] Ishak, S., H. C. Shin, B. K. Sridhar, and Z. Zhang. Characterization and Development of Truck Axle Load Spectra for Future Implementation of Pavement Design Practices in Louisiana. In Transportation Research Record: Journal of the Transportation Research Board, No. 2153, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 121–129.
[7] Haider, S. W., R. S. Harichandran, and M. B. Dwaikat. Effect of Axle Load Measurement Errors on Pavement Performance and Design Reliability. In Transportation Research Record: Journal of the Transportation Research Board, No. 2160, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 107– 117.
[8] Romanoschi, S. A., S. Momin, S. Bethu, L. Bendana. Development of Traffic Inputs for the new ME Pavement Design Guide: a Case Study. Journal of Transportation Engineering, Vol. 2256, 2011, pp. 142–150.
[9] Smith, B. C., and B. K. Diefenderfer. Analysis of Virginia-Specific Traffic Data for Use with the Mechanistic-Empirical Pavement Design Guide. In Transportation Research Record: Journal of the Transportation Research Board, No. 2154, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 100– 107.
[10] Darter, M., L. Titus-Glover, and D. Wolf. Development of a Traffic Data Input System in Arizona for the MEPDG. Final Report, Report No. FHWA-AZ-13-672, 2013, Arizona Department of Transportation, Phoenix, AZ.
[11] Islam, M. R., R. A. Tarefder, and I. Syed. Measurements of Lateral Distribution of Vehicle Wheels and its Effect on Fatigue Life of Asphalt Concrete. 3rd International Conference on Transportation Infrastructure (ICTI), April 22-25, 2014, Pisa, Italy, pp. 379–383.