Panel Data Models for Pavement Friction of Major Preventive Maintenance Treatments
Publication: International Journal of Geomechanics
Volume 19, Issue 8
Abstract
Although accurate evaluation of pavement friction promises significant safety benefits to highway agencies, the development of such models has proven to be challenging due to the lack of complete and quality pavement surface data for friction studies. In this study, the state-of-the-art three-dimensional (3D) laser imaging technology and the Grip Tester, which is a type of continuous friction measurement equipment (CFME), are used to collect 1-mm 3D pavement surface data and friction data, respectively, at highway speed in the field; whereas the Aggregate Imaging System (AIMS) is used in the laboratory to analyze the surface characteristics of aggregates. Forty-five pavement sites, including six major preventive maintenance (PM) treatments and seven typical types of aggregates in Oklahoma, are identified as the testing beds. Multiple field data collection events have been performed from 2015 to 2017. Panel data analysis (PDA), which is able to investigate the differences of cross-sectional information (the time series changes over time), is conducted to identify the most significant influencing factors for pavement friction prediction model development. Statistical analyses indicate that the random-effects panel model outperforms the fixed-effects model and the traditional ordinary least-squares regression model. The panel model developed in this study could assist decision makers in the selection of PM treatments and aggregates for optimized skid resistance performance.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This work is supported by the Oklahoma DOT (ODOT) under research project “Development of Aggregate Characteristics-Based Preventive Maintenance Treatments Using 3D Laser Imaging and Aggregate Imaging Technology for Optimized Skid Resistance of Pavements.” The opinions expressed in the paper are those of the authors, who are responsible for the accuracy of the facts and data in this paper, and their opinions do not necessarily reflect the official policies of the sponsoring agency. This paper does not constitute a standard, regulation, or specification.
References
Anupam, K., S. K. Srirangam, T. Scarpas, and C. Kasbergen. 2013. “Influence of temperature on tire–pavement friction: Analyses.” Trans. Res. Rec. 2369 (1): 114–124. https://doi.org/10.3141/2369-13.
ASTM. 2006. Standard test method for resistance to degradation of Small-Size coarse aggregate by abrasion and impact in the Los Angeles machine. C131/C131M-14. West Conshohocken, PA: ASTM.
ASTM. 2011. Standard test method for skid resistance of paved surfaces using a full-scale tire. E274/E274M-11. West Conshohocken, PA: ASTM.
ASTM. 2015. Standard test method for resistance of fine aggregate to degradation by abrasion in the Micro-Deval apparatus. D7428-15. West Conshohocken, PA: ASTM.
ASTM. 2017. Standard test method for resistance of coarse aggregate to degradation by abrasion in the Micro-Deval apparatus. D6928-17. West Conshohocken, PA: ASTM.
ASTM. 2018. Standard practice for conducting an interlaboratory study to determine the precision of a test method. E691-18. West Conshohocken, PA: ASTM.
Bazlamit, S., and F. Reza. 2005. “Changes in asphalt pavement friction components and adjustment of skid number for temperature.” J. Transp. Eng. 131 (6): 470–476. https://doi.org/10.1061/(ASCE)0733-947X(2005)131:6(470).
Bledsoe, J. 2015. Missouri demonstration project: The use of high-friction surface treatments on Missouri highways. Final Rep. Washington, DC: FHWA.
Breusch, T. S., and A. R. Pagan. 1980. “The Lagrange multiplier test and its applications to model specification in econometrics.” Rev. Econ. Stud. 47 (1): 239–253. https://doi.org/10.2307/2297111.
Cenek, P. D., P. Carpenter, N. Jamieson, and P. Stewart. 2004. Prediction of skid resistance performance of chipseal roads in New Zealand. Research Rep. 256. Wellington, NZ: Transfund New Zealand.
Croissant, Y., and G. Millo. 2008. “Panel data econometrics in R: The PLM package.” J. Stat. Software 27 (2): 1–43. https://doi.org/10.18637/jss.v027.i02.
Csathy, T. I., W. C. Burnett, and M. D. Armstrong. 1968. State-of-the-art of skid resistance research. Highway Research Board Special Rep. 95. Washington, DC: Highway Research Board.
FHWA (Federal Highway Administration). 2017. “Pavement Preservation (When, Where, and How).” Washington, DC: FHWA.
Fowler, D. W., and M. M. Rached. 2012. “Polish resistance of fine aggregates in Portland cement concrete pavements.” Transp. Res. Rec. 2267 (1): 29–36. https://doi.org/10.3141/2267-03.
Fuentes, L., M. Gunaratne, and D. Hess. 2010. “Evaluation of the effect of pavement roughness on skid resistance.” J. Transp. Eng. 136 (7): 640–653. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000118.
Fuentes, L. G. 2009. “Investigation of the factors influencing skid resistance and the international friction index.” Ph.D. dissertation, Univ. of South Florida.
Gates, L., E. Masad, R. Pyle, and D. Bushee. 2011. Aggregate imaging measurement system 2 (AIMS2). Final Report (Rep. No. FHWA-HIF-11-030). Washington, DC: FHWA.
Greene, W. H. 2012. Econometric analysis. 7th ed., 420. Upper Saddle River, NJ: Pearson.
Greer, M., and M. Heitzman. 2017. Evaluation of the AIMS2 and Micro-Deval to characterize aggregate friction properties. NCAT Rep. 17-02. Auburn, AL: NCAT.
Gudimettla, J., L. A. Myers, and C. Paugh. 2006. AIMS: The future in rapid, automated aggregate shape and texture measurement. Washington, DC: National Academies Press.
Hall, J. W., and A. N. Hanna. 2009. Guide for pavement friction: Background and research. Washington, DC: Transportation Research Board.
Hsiao, C. 2006. “Panel data analysis–Advantages and challenges.” SSRN Electr. J. https://doi.org/10.2139/ssrn.902657.
Hsiao, C., K. Lahiri, L. Lee, and M. H. Pesaran, eds. 1999. Analysis of panels and limited dependent variable models. Cambridge, UK: Cambridge University Press.
Ioannidis, J. P. 2007. “Why most published research findings are false: Authors reply to Goodman and Greenland.” PLoS Med. 4 (6): e215. https://doi.org/10.1371/journal.pmed.0040215.
Jahromi, S. G., S. M. Mortazavi, S. Voussough, and L. Yingjian. 2011. “Evaluation of pavement temperature on skid frictional of asphalt concrete surface.” Int. J. Pavement Eng. 12 (1): 47–58. https://doi.org/10.1080/10298436.2010.501864.
Jayawickrama, P., and B. Thomas. 1998. “Correction of field skid measurements for seasonal variations in Texas.” Transp. Res. Rec. 1639 (1): 147–154. https://doi.org/10.3141/1639-16.
Ji, Y., T. Nantung, and B. Tompkins. 2015. “Evaluation for UTBWC on SR-11 as pavement preservation treatment: A case study.” Int. J. Pavement Res. Technol. 8 (4): 267–275. https://doi.org/10.6135/ijprt.org.tw/2015.8(4).267.
Kanafi, M. M., A. Kuosmanen, T. K. Pellinen, and A. J. Tuononen. 2015. “Macro- and micro-texture evolution of road pavements and correlation with friction.” Int. J. Pavement Eng. 16 (2): 168–179. https://doi.org/10.1080/10298436.2014.937715.
Kassem, E., A. Awed, E. A. Masad, and D. N. Little. 2013. “Development of predictive model for skid loss of asphalt pavements.” Transp. Res. Rec. 2372 (1): 83–96. https://doi.org/10.3141/2372-10.
Knaub, J. R., Jr. 1987. “Practical interpretation of hypothesis tests: Letter to the editor.” Am. Statistician 41 (3): 246–247.
Kokkalis, A. G., and O. K. Panagouli. 1998. “Fractal evaluation of pavement skid resistance variations. I: Surface wetting.” Chaos, Solitons Fractals 9 (11): 1875–1890. https://doi.org/10.1016/S0960-0779(97)00138-0.
Kotek, P., and Z. Florková. 2014. “Comparison of the skid resistance at different asphalt pavement surfaces over time.” Procedia Eng. 91: 459–463. https://doi.org/10.1016/j.proeng.2014.12.026.
Lane, B., C. Rogers, and S. Senior. 2000. “The Micro-Deval test for aggregates in asphalt pavement.” In Proc., 8th Annual Symp. of Int. Center for Aggregate Research. Denver, CO: International Center for Aggregates Research.
Li, Q. J., G. Yang, K. C. P. Wang, Y. Zhan, D. Merritt, and C. Wang. 2016. “Effectiveness and performance of high friction surface treatments at a national scale.” Can. J. Civ. Eng. 43 (9): 812–821. https://doi.org/10.1139/cjce-2016-0132.
Luce, A., E. Mahmoud, E. Masad, and A. Chowdhury. 2007. “Relationship of aggregate microtexture to asphalt pavement skid resistance.” J. Test. Eval. 35 (6): 578–588. https://doi.org/10.1520/JTE101080.
Luo, Y. 2003. “Effect of pavement temperature on frictional properties of hot-mix-asphalt pavement surfaces at the Virginia smart road.” M.Sc. dissertation, VA Polytechnic Institute and State Univ.
Mahmoud, E. 2005. “Development of experimental methods for the evaluation of aggregate resistance to polishing, abrasion, and breakage.” M.Sc. thesis, Texas A&M Univ.
Masad, E., S. Saadeh, T. Al-Rousan, E. Garboczi, and D. Little. 2005. “Computations of particle surface characteristics using optical and X-ray CT images.” Comput. Mater. Sci. 34 (4): 406–424. https://doi.org/10.1016/j.commatsci.2005.01.010.
Moaveni, M., E. Mahmoud, E. Ortiz, E. Tutumluer, and S. Beshears. 2014. “Use of advanced aggregate imaging systems to evaluate aggregate resistance to breakage, abrasion, and polishing.” Transp. Res. Rec. 2401 (1): 1–10. https://doi.org/10.3141/2401-01.
Moravec, M. 2013. “High friction surface treatments at high-crash horizontal curves.” Arizona Pavements/Materials Conf. Accessed December 12, 2017. https://pavement.engineering.asu.edu/wp-content/uploads/2013/12/High-Friction-Surface-Treatments-Mike-Moravec.pdf.
Neaylon, K. 2009. “The PAFV test and road friction.” In Proc., AAPA 13th Int. Flexible Pavements Conf. Port Melbourne, VIC, Australia: Australian Asphalt Pavement Association.
Noyce, D., H. Bahia, J. Yambo, and G. Kim. 2005. Incorporating road safety into pavement management: Maximizing asphalt pavement surface friction for road safety improvements. Madison, WI: Traffic Operations and Safety (TOPS) Laboratory.
Park, H. M. 2011. “Practical guides to panel data modeling: A step by step analysis using Stata.” Tutorial Working Paper. Niigata, Japan: Graduate School of International Relations, International Univ. of Japan.
Qi, Y., B. Smith, and J. Guo. 2007. “Freeway accident likelihood prediction using a panel data analysis approach.” J. Transp. Eng. 133 (3): 149–156. https://doi.org/10.1061/(ASCE)0733-947X(2007)133:3(149).
Ranstam, J. 2012. “Why the P-value culture is bad and confidence intervals a better alternative.” Osteoarthritis Cartilage 20 (8): 805–808. https://doi.org/10.1016/j.joca.2012.04.001.
Rezaei, A., E. Masad, and A. Chowdhury. 2011. “Development of a model for asphalt pavement skid resistance based on aggregate characteristics and gradation.” J. Transp. Eng. 137 (12): 863–873. https://doi.org/10.1061/(ASCE)TE.1943-5436.0000280.
Rezaei, A., E. Masad, A. Chowdhury, and P. Harris. 2009. “Predicting asphalt mixture skid resistance by aggregate characteristics and gradation.” Transp. Res. Rec. 2104 (1): 24–33. https://doi.org/10.3141/2104-03.
Roberts, D., and F. Roberts. 2012. “Correlation coefficients–MathBitsNotebook.” Accessed August 10, 2017. https://mathbitsnotebook.com/Algebra2/Statistics/STCorrelationCoefficients.html.
Rogers, C. 1998. “Canadian experience with the micro-Deval test for aggregates.” Eng. Geol. 13: 139–147. https://doi.org/10.1144/GSL.ENG.1998.013.01.11.
Smith, K. L., J. W. Hall, and P. Littleton. 2009. Texturing of concrete pavements. NCHRP Rep. 634. Washington, DC: National Academies of Sciences.
Susanna, A., M. Crispino, F. Giustozzi, and E. Toraldo. 2017. “Deterioration trends of asphalt pavement friction and roughness from medium-term surveys on major Italian roads.” Int. J. Pavement Res. Technol. 10 (5): 421–433. https://doi.org/10.1016/j.ijprt.2017.07.002.
Wang, H., and Z. Wang. 2013. “Evaluation of pavement surface friction subject to various pavement preservation treatments.” Constr. Build. Mater. 48 (Nov): 194–202. https://doi.org/10.1016/j.conbuildmat.2013.06.048.
Wang, K. C. 2011. “Elements of automated survey of pavements and a 3D methodology.” J. Mod. Transp. 19 (1): 51–57. https://doi.org/10.1007/BF03325740.
Washington, S. P., M. G. Karlaftis, and F. Mannering. 2011. Statistical and econometric methods for transportation data analysis. 2nd ed. Boca Raton, FL: CRC Press.
Wasserstein, R. L., and N. A. Lazar. 2016. “The ASA’s statement on p-values: Context, process, and purpose.” Am. Statistician 70 (2): 129–133. https://doi.org/10.1080/00031305.2016.1154108.
Information & Authors
Information
Published In
Copyright
© 2019 American Society of Civil Engineers.
History
Received: May 28, 2018
Accepted: Jan 8, 2019
Published online: May 16, 2019
Published in print: Aug 1, 2019
Discussion open until: Oct 16, 2019
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.