Modeling Pavement Performance Based on LTPP Database for Flexible Pavements

Abstract

In many countries, incredible investments have been made in constructing roads that require conducting periodic evaluation and timely maintenance and rehabilitation (M&R) plan to keep the network operating under acceptable level of service. The timely M&R plan necessitates accurately predicting pavement performance, which is an essential element of road infrastructure asset management systems or Pavement Management Systems (PMS). Consequently, there is always a need to develop and to update performance prediction models embedded in PMS applications. This study focuses in developing distress prediction models for flexible pavements located in non-freeze climatic zone, which represent most of developing countries such as Egypt, using data extracted from the Long-Term Pavement Performance (LTPP) program. Ten distress performance prediction models were developed in this study for both wet- and dry-non freeze climatic zones, which are alligator (Fatigue) cracking, longitudinal cracking, transverse cracking, ravelling, bleeding, and rut depth models. These models can play an important role assisting decision makers in predicting pavement performance, identifying M&R needs, rational budget planning and resource allocation.

Keywords

• Prediction models
• distress models
• ltpp
• statistical modeling
• flexible pavement
• non-freeze climatic zone

Modeling Pavement Performance Based on LTPP Database for Flexible Pavements

Abstract

In many countries, incredible investments have been made in constructing roads that require conducting periodic evaluation and timely maintenance and rehabilitation (M&R) plan to keep the network operating under acceptable level of service. The timely M&R plan necessitates accurately predicting pavement performance, which is an essential element of road infrastructure asset management systems or Pavement Management Systems (PMS). Consequently, there is always a need to develop and to update performance prediction models embedded in PMS applications. This study focuses in developing distress prediction models for flexible pavements located in non-freeze climatic zone, which represent most of developing countries such as Egypt, using data extracted from the Long-Term Pavement Performance (LTPP) program. Ten distress performance prediction models were developed in this study for both wet- and dry-non freeze climatic zones, which are alligator (Fatigue) cracking, longitudinal cracking, transverse cracking, ravelling, bleeding, and rut depth models. These models can play an important role assisting decision makers in predicting pavement performance, identifying M&R needs, rational budget planning and resource allocation.

Keywords

• Prediction models
• distress models
• ltpp
• statistical modeling
• flexible pavement
• non-freeze climatic zone

References

1. [1] Haas, R., Hudson, R., Zaniewski, J., Modern Pavement Management. Krieger Publishing Company, Malabor Florida, 1994.
2. [2] Stantec-HPMA Manual, Highway Pavement Management Application (HPMA). User Documentation, V4.50. GARBLT Research Project in Egypt, Technical Consultations Bureau, Applied Engineering Technologies (TCB/AET), Cambridge, ON, Canada, 2001.
3. [3] George, K. P., Rajagopal, A.S., Lim, L. K., Models for Predicting Pavement Deterioration. Transportation Research Record 1215, 1-7, 1989.
4. [4] Li, N., Haas, R., Xie, W-C, Investigation of Relationship Between Deterministic and Probabilistic Prediction Models in Pavement Management. Transportation Research Record 1592, 70–79, 1997.
5. [5] Zimmerman, K. A., Testa, D. M., An Evaluation of Idaho Transportation Department Needs for Maintenance Management and Pavement Management Software Tools, 2008.
6. [6] Naiel, A. K., Flexible Pavement Rut Depth Modeling For Different Climate Zones. Ph.D. Thesis, Wayne State University, 2010.
7. [7] Kulkarni R.B., Miller R.W., Pavement Management Systems Past, Present, and Future. Transportation Research Record 1853, 65–71, 2002.
8. [8] Li, N., Xie, W-C; Haas, R., Reliability-Based Processing of Markov Chains for Modeling Pavement Network Deterioration. Transportation Research Record 1524, 203–213, 1996.

9. [9] Porras-Alvarado, J. D., Probabilistic Approach to Modeling Pavement Performance using IRI Data. In Proceedings of 93rd Annual Meeting of the Transportation Research Board, Washington, DC, 2014.
10. [10] ARA Inc. Guide for Mechanistic-Empirical Design of New and Rehabilitated Pavement Structures. Final Documents, NCHRP, Champaign, 2004.
11. [11] Göransson, N. G., Den Svenska Nationella LTPP Database, VTI, 2009.
12. [12] Asphalt Institute, Research and Development of the Asphalt Institute’s Thickness Design Manual (MS1), 9th Ed. Research Report: 82-2, 1982.
13. [13] Ali, H. A., Tayabji, S. D., Evaluation of Mechanistic-Empirical Performance Prediction Models for Flexible Pavement. Transportation Research Record, 1629, 169-180, 1989. http://Doi: 10.1016/j.sbspro.2012.06.1012.
14. [14] Ker, H., Lee, Y., Wu, P., Development of Fatigue Cracking Performance Prediction Models for Flexible Pavements Using LTPP Database. Transportation Research Board 86th Annual Meeting, Washington, D.C, January 21-25, 2007.
15. [15] George, K., Vepa, T., Shekhran, A., Prediction of Pavement Remaining Life. 1996.
16. [16] Ali, B., Numerical Model for the Mechanical Behavior of Pavement: Application to the Analysis of Rutting. Ph.D. Thesis, University of Science and Technology Lille, 2006.
17. [17] Federal Highway Administration (FHWA) 2002. Available from internet: https://www.fhwa.dot.gov/research/tfhrc/programs/infrastructure/pavements/ltpp/ (Accessed August 2017).
18. [18] Long-Term Pavement Performance (LTPP), 2017. Available from: https://infopave.fhwa.dot.gov/ (Accessed on September 19, 2017).
19. [19] Abo-Hashema, M. A., Sharaf, E. A., Development of Maintenance Decision Model for Flexible Pavements. International Journal of Pavement Engineering, 10 (3), 173-187, 2009.
20. [20] Shahin, M. Y., Kohn, S. D., Pavement Maintenance Management for Roads and Parking Lots. United States Army Corps of Engineers, Technical Report: M-294, 1981.
21. [21] This reference must be added to the list because it is cited in the manuscript on page 10.