Assessment of Construction Smoothness Specification Pay Factor Limits Using Artificial Neural Network Modeling
Publication: Journal of Transportation Engineering
Volume 131, Issue 7
Abstract
Many state highway agencies are using quality control/quality assurance construction smoothness specifications that provide for contractors’ pay to be proportional to the riding comfort of the constructed new pavement. However, in many cases, the pay factor limits are based on subjective engineering judgment rather than rational analysis of the declining riding comfort of newly constructed pavements. This study used the artificial neural network methodology to develop time-dependent roughness prediction models for three types of pavements: Portland cement concrete pavement, asphalt overlay over concrete pavement, and asphalt pavement. The relationship of various pay factor limits and future roughness progression and the pavement service life were assessed. Rational pay factor limits were then developed for the zero blanking band profile index of the California Profilograph measurements employed in the construction smoothness specifications based on the predicted future riding comfort of the newly constructed pavements.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work was supported by the Joint Transportation Research Program (JTRP) administered by the Indiana Department of Transportation and Purdue University. The writers wish to thank Mr. Dave Ward, Dr. Samy Noureldin, Mr. Greg Pankow, Mr. Bill Flora, and Mr. Lee Gallivan for serving as JTRP Study Advisory Committee members and for providing their help and advice during the research.
References
Carey, W. N., and Irick, P. E. (1960). “The pavement serviceability-performance concept.” Transp. Res. Rec., 250, Transportation Research Board, Washington, D.C., 40–58.
Devore, J., Hossain, M., and Parcells, W. (1995). “Automated system for pavement profile analysis from profilograph traces.” Transp. Res. Rec., 1505, Transportation Research Board, Washington, D.C., 47–56.
Federal Highway Administration (FHWA). (1998). “Status of the nation’s highways, bridges, and transit: conditions and performance.” Rep. to Congress, Washington, D.C. ⟨http://www.fhwa.dot.gov////policy/1999cpr/index.htm⟩, accessed August 9, 2003).
Fernando, E. G. (1998). “Development of a profile-based smoothness specification for asphalt concrete overlays.” Project Summary Rep. No. 1378-S, Texas Transportation Institute, Texas A&M Univ., College Station, Tex.
Hoerner, T. E., Darter, M. I., Khazanovith, L., Titus-Glover, L., and Smith, K. L. (2000). “Improved prediction models for PCC pavement performance related specifications, Volume I.” Final Rep. No. FHWA-RD-00-130, Federal Highway Administration, Washington, D.C.
Janoff, M. S. (1990). “The prediction of pavement ride quality from profile measurements of pavement roughness.” ASTM STP 1031, Philadelphia, 259–267.
Kajner, L., Kirlanda, M., and Sparks, G. (1996). “Development of Bayesian regression model to predict hot-mix asphalt concrete overlay roughness.” Transp. Res. Rec., 1539, Transportation Research Board, Washington, D.C., 125–131.
Owusu-Aabio, S. (1998). “Effect of neural network topology on flexible pavement cracking prediction.” Comput. Aided Civ. Infrastruct. Eng., 13, 349–355.
Parcells, W. H. (2001). “Control of pavement trueness in kansas.” Eleventh Interim Rep. No. KDOT 73-1, Kansas Dept. of Transportation, Topeka, Kan.
Paterson, W. D. O. (1989). “A transferable causal model for predicting roughness progression in flexible pavements.” Transp. Res. Rec., 1215, Transportation Research Board, Washington, D.C., 70–84.
Pellinen, T. K., and Chou, S. (2003). “Evaluation of INDOT construction smoothness specifications.” Draft Final Rep. No. FHWA/IN/JTRP-2003/8 Indiana Department of Transportation, Indianapolis.
Sebaaly, P., Law, S., and Hand, A. (1995). “Performance models for flexible pavement maintainance treatments.” Transp. Res. Rec., 1508, Transportation Research Board, Washington, D.C., 9–21.
Shafizadeh, K., and Mannering, F. (2003). “Acceptability of pavement roughness on urban highways by the driving public.” Transp. Res. Rec., 1860, Transportation Research Board, Washington, D.C., 187–193.
Siddique, Z. Q., Hossain, M., Devore, J., and Parcells, W. H. (2003). “Effect of curling on as-constructed and early life smoothness of PCC pavements.” Proc., 2003 Mid-Continent Transportation Research Symp., Ames, Iowa.
Sinha, K. C., Labi, S., Li, Z., and Islam, M. S. (2000). IndiPave 2000, Purdue Univ., West Lafayette, Ind.
Smith, K. L., Smith, K. D., Evans, L. D., Hoerner, T. E., Darter, M. I., and Woodstrom, J. H. (1997). “Smoothness specifications for pavements.” Final Rep. No. NCHRP 1-31, Transportation Research Record, National Research Council, Washington, D.C.
Smith, K. L., Titus-Glover, L., and Evans, L. D. (2002). “Pavement smoothness index relationships.” Final Rep. No. FHWA-RD-02-057, Federal Highway Administration, Washington, D.C.
Tsoukalas, L. H., and Uhrig, R. E. (1997). Fuzzy and neural approaches in engineering, Wiley, New York.
Information & Authors
Information
Published In
Copyright
© 2005 ASCE.
History
Received: Dec 17, 2003
Accepted: Sep 28, 2004
Published online: Jul 1, 2005
Published in print: Jul 2005
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.