Research Article
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Development of pavement performance prediction model for bituminous hot mix asphalt on interurban road networks

Year 2017, Volume: 23 Issue: 6, 718 - 725, 15.12.2017

Abstract

The
correct prediction of the deterioration of bituminous hot mix asphalt (HMA),
which is a significant substructure investment for roads, is an indispensable
element in the correct sorting of the budget allocated for maintenance and
repair. This study has developed a pavement performance prediction model for
state roads and intercity roads hot mix asphalt (HMA) coated under the
responsibility of General Directorate of Highways (KGM) for capable of
performance forecast for next year. International roughness index (IRI) were
used as a performance indicator of pavements. Pavement condition index (PCI) of
the road sections (year of construction of the road known by KGM), using
existing pavement distresses data by PAVER system, were obtained. The
prediction performance model was developed depending on the age and PCI of the road
sections using deterministic regression model technique. Then, mathematical
relationship was determined between PCI and IRI on the same road section. The
obtained mathematical relationship is integrated into the prediction
performance model. A prediction model determines the pavements IRI values for
the coming years, based on independent variables of measured IRI value and year's
estimated performance, were obtained. The accuracy of the IRI deterioration prediction
model was controlled by the data sets not used in the modeling studies.

References

  • AASHTO. Guide for Design of Pavement Structures. Washington, USA, AASHTO, 1993.
  • Haas R, Hudson WR, Zaniewski JP. Modern Pavement Management, Florida, USA, Krieger Pub. Co.,1994.
  • Moazami D, Behbahani H, Muniandy R. “Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic”. Expert Systems with Applications. 38(10), 12869-12879, 2011.
  • Yang J, Lu J. “Gunaratne M, Xiang Q. Overall Pavement Condition Forecasting Using Neural Networks-an Application to Florida Highway Network”. 82nd Annual Meeting of the Transportation Research Board, Washington, USA, 12-16 January 2003.
  • Shahin MY. Pavement Management for Airports, Roads and Parking Lots, New York, USA, Springer, 2005.
  • Ziari H, Sobhani J, Ayoubinejad J, Hartmann T. “Prediction of IRI in short and long terms for flexible pavements: ANN and GMDH methods”. International Journal of Pavement Engineering, 17(9), 776-788, 2016.
  • Salem O, El-Assaly A, Abou-Rizk S. “Performance prediction models of pavement highway network in alberta”. 82nd Annual Meeting of the Transportation Research Board, Washington, USA, 12-16 January 2003.
  • Khattak MJ, Landry C, Veazey J, Zhang Z. “Rigid and composite pavement index-based performance models for network pavement management system in the state of louisiana”. International Journal of Pavement Engineering, 14(7), 612-628, 2013.
  • Chou E, Pulugurta H, Datta D. “Pavement Forecasting Models”. Ohio Department of Transportation Columbus, OH, Scientific Report, 2008.
  • Chen C, Zhang J. “Comparisons of IRI-Based pavement deterioration prediction models using new mexico pavement data”. Geo-Frontiers Congress, Dallas, Texas, USA, 13-16 March 2011.
  • Luo Z. “Pavement performance modelling with an auto-regression approach”. International Journal of Pavement Engineering, 14(1), 85-94, 2013.
  • Ahmed K, Abu-Lebdeh G, Lyles RW. “Prediction of pavement distress ındex with limited data on causal factors: An auto-regression approach”. International Journal of Pavement Engineering, 7(1), 23-35, 2006.
  • Attoh-Okine NO, Cooger K, Mensah S. “Multivariate adaptive regression (MARS) and hinged hyperplanes (hhp) for doweled pavement performance modeling”. Construction and Building Materials, 23(9), 3020-3023, 2009.
  • Parvini M. “Artificial neural network modeling of pavement performance using expert judgement”. Road Materials and Pavement Design, 3(4), 373-384, 2002.
  • Khan MU, Williams DJ, Ferreira L, Mesbah M. “Developing a new road deterioration model ıncorporating flooding”. Proceedings of the ICE-Transport, 167(5), 322-333, 2014.
  • Pulugurta H, Shao Q, Chou YJ. “Pavement condition prediction using markov process”. Journal of Statistics and Management Systems, 12(5), 853-871, 2009.
  • Lethanh N, Adey BT. “Use of exponential hidden markov models for modelling pavement deterioration”. International Journal of Pavement Engineering, 14(7), 645-654, 2013.
  • Park ES, Smith RE, Freeman TJ, Spiegelman CH. “A bayesian approach for ımproved pavement performance prediction”. Journal of Applied Statistics, 35(11), 1219-1238, 2008.
  • Hong HP, Wang SS. “Stochastic modeling of pavement performance”. International Journal of Pavement Engineering, 4(4), 235-243, 2003.
  • Hassan R, Lin O, Thananjeyan A. “A comparison between three approaches for modelling deterioration of five pavement surfaces”. International Journal of Pavement Engineering, 18(1), 26-35, 2015.
  • Pan NF, Ko CH, Yang MD, Hsu KC. “Pavement performance prediction through fuzzy regression”. Expert Systems with Applications. 38(8), 10010-10017, 2011.
  • Karaşahin M, Terzi S. “Performance model for asphalt concrete pavement based on the fuzzy logic approach”. Transport, 29(1), 18-27, 2014.
  • Attoh-Okine NO. “Analysis of Learning Rate and Momentum Term in Backpropagation Neural Network Algorithm Trained to Predict Pavement Performance”. Advances in Engineering Software, 30(4), 291-302, 1999.
  • Terzi S. “Modeling the pavement serviceability ratio of flexible highway pavements by artificial neural networks”. Construction and Building Materials, 21(3), 590–593, 2007.
  • Terzi S. “Modeling for pavement roughness using the ANFIS approach”. Advances in Engineering Software, 57, 59-64, 2013.
  • Attoh-Okine NO, Mensah S, Nawaiseh M. “A new technique for using multivariate adaptive regression splines (MARS) in pavement roughness prediction”. Proceedings of the Institution of Civil Engineers-Transport, 156(1), 51-55, 2003.
  • Ahmed A, Labi S, Li Z, Shields T. “Aggregate and disaggregate statistical evaluation of the performance-based effectiveness of long-term pavement performance specific pavement study-5 (LTPP SPS-5) flexible pavement rehabilitation treatments”. Structure and Infrastructure Engineering, 9(2), 172-187, 2013.
  • Mubaraki M. “Predicting Pavement Condition Deterioration for the Saudi Inter-Urban Road Network”. GeoHunan International Conference, Changsha, Hunan, China, 3-6 August 2009.
  • Amador-Jiménez LE, Mrawira D. “Reliability-Based initial pavement performance deterioration modelling”. International Journal of Pavement Engineering, 12(2), 177-186, 2011.
  • Fekpe E, Attoh-Okine NO. “Deterioration modelling for lateritic-base flexible pavements”. Construction and Building Materials, 9(3), 159-163, 1995.
  • Bennett C, Petersen W. A Guide to Calibration and Adaptation, Washington, DC, USA, PIARC, 1999.
  • Braga A, Čygas D. “Adaptation of pavement deterioration models to lithuanian automobile roads”. Journal of Civil Engineering and Management, 8(3), 214-220, 2002.
  • Odoki JB, Anyala M, Bunting E. “HDM-4 adaptation for strategic analysis of UK local roads”. Proceedings of the ICE-Transport, 166(2), 65-78, 2013.
  • Martin TC. “Heavy vehicle road wear on sealed unbound granular roads”. Proceedings of the ICE-Transport, 164(1), 13-22, 2011.
  • Jorge D, Ferreira A. “Road network pavement maintenance optimisation using the hdm-4 pavement performance prediction models”. International Journal of Pavement Engineering, 13(1), 39-51, 2012.
  • Chootinan P, Chen A, Horrocks MR, Bolling D. “A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach”. Transportation Research Part A: Policy and Practice, 40(9),725-743, 2006.
  • Chi S, Hwang J, Arellano M, Zhang Z, Murphy M. “Development of network-level project screening methods supporting the 4-year pavement management plan in Texas”. Journal of Management in Engineering, 29(4), 482-494, 2013.
  • Chou JS, Le TS. “Reliability-Based performance simulation for optimized pavement maintenance”. Reliability Engineering & System Safety, 96(10), 1402-1410, 2011.
  • Meneses S, Ferreira A. “Flexible pavement maintenance programming considering the minimisation of maintenance and rehabilitation costs and the maximisation of the residual value of pavements”. International Journal of Pavement Engineering, 16(7), 571-586, 2014.
  • İncegül M, Ergün M. “An ıntegrated graphical user ınterface for pavement deterioration modeling”. Scientific Research and Essay, 6(17), 3649-3656, 2011.
  • Güngör AG, Hacak B, Ünal EN. “Üstyapı yönetim sistemi KGM uygulamaları”. 2. Karayolu Ulusal Kongresi, Ankara, Türkiye, 11-13 Ekim 2011.
  • Park K, Thomas NE, Wayne Lee K. “Applicability of the international roughness ındex as a predictor of asphalt pavement condition”. Journal of Transportation Engineering, 133(12), 706-709, 2007.

Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi

Year 2017, Volume: 23 Issue: 6, 718 - 725, 15.12.2017

Abstract

Önemli
bir altyapı yatırımı olan bitümlü sıcak karışım (BSK) üstyapıların
bozulmalarının doğru tahmin edilmesi, bakım ve onarım için ayrılan bütçenin
doğru olarak belirlenmesinde vazgeçilmez bir unsurdur. Çalışmada, Karayolları
Genel Müdürlüğünün (KGM) sorumluluğunda bulunan devlet yolu ve il yolu
statüsündeki BSK kaplamalı yollarda, gelecek yıllara ait performans tahmini
yapabilen bir üstyapı performans tahmin modeli geliştirilmiştir. Üstyapıların
performans göstergesi olarak uluslararası düzgünsüzlük indeksi (IRI)
kullanılmıştır. KGM tarafından yapım yılı bilinen yollarda mevcut üstyapı
bozulma bilgileri kullanılarak PAVER sistemi yardımıyla kesimlerin üstyapı
durum indeksi (PCI) bilgileri elde edilmiştir. Kesimlerin PCI ve yaşlarına
bağlı olarak deterministik regresyon modeli tekniği kullanılarak tahmin modeli
oluşturulmuştur. Sonrasında, aynı yol kesimlerinde PCI ve IRI arasındaki
matematiksel ilişki ortaya konmuştur. Elde edilen bu matematiksel ilişki oluşturulan
gelecek tahmin modeline entegre edilerek, ölçülen IRI değeri ve performansı
tahmin edilecek yıl bağımsız değişkenlerine bağlı olarak üstyapıların gelecek
yıllara ait IRI değerlerini belirleyen bir tahmin modeli elde edilmiştir. IRI
bozulma tahmin modelinin doğruluğu, modelleme çalışmalarında hiçbir şekilde
kullanılmayan veri setleri ile kontrol edilmiştir.

References

  • AASHTO. Guide for Design of Pavement Structures. Washington, USA, AASHTO, 1993.
  • Haas R, Hudson WR, Zaniewski JP. Modern Pavement Management, Florida, USA, Krieger Pub. Co.,1994.
  • Moazami D, Behbahani H, Muniandy R. “Pavement rehabilitation and maintenance prioritization of urban roads using fuzzy logic”. Expert Systems with Applications. 38(10), 12869-12879, 2011.
  • Yang J, Lu J. “Gunaratne M, Xiang Q. Overall Pavement Condition Forecasting Using Neural Networks-an Application to Florida Highway Network”. 82nd Annual Meeting of the Transportation Research Board, Washington, USA, 12-16 January 2003.
  • Shahin MY. Pavement Management for Airports, Roads and Parking Lots, New York, USA, Springer, 2005.
  • Ziari H, Sobhani J, Ayoubinejad J, Hartmann T. “Prediction of IRI in short and long terms for flexible pavements: ANN and GMDH methods”. International Journal of Pavement Engineering, 17(9), 776-788, 2016.
  • Salem O, El-Assaly A, Abou-Rizk S. “Performance prediction models of pavement highway network in alberta”. 82nd Annual Meeting of the Transportation Research Board, Washington, USA, 12-16 January 2003.
  • Khattak MJ, Landry C, Veazey J, Zhang Z. “Rigid and composite pavement index-based performance models for network pavement management system in the state of louisiana”. International Journal of Pavement Engineering, 14(7), 612-628, 2013.
  • Chou E, Pulugurta H, Datta D. “Pavement Forecasting Models”. Ohio Department of Transportation Columbus, OH, Scientific Report, 2008.
  • Chen C, Zhang J. “Comparisons of IRI-Based pavement deterioration prediction models using new mexico pavement data”. Geo-Frontiers Congress, Dallas, Texas, USA, 13-16 March 2011.
  • Luo Z. “Pavement performance modelling with an auto-regression approach”. International Journal of Pavement Engineering, 14(1), 85-94, 2013.
  • Ahmed K, Abu-Lebdeh G, Lyles RW. “Prediction of pavement distress ındex with limited data on causal factors: An auto-regression approach”. International Journal of Pavement Engineering, 7(1), 23-35, 2006.
  • Attoh-Okine NO, Cooger K, Mensah S. “Multivariate adaptive regression (MARS) and hinged hyperplanes (hhp) for doweled pavement performance modeling”. Construction and Building Materials, 23(9), 3020-3023, 2009.
  • Parvini M. “Artificial neural network modeling of pavement performance using expert judgement”. Road Materials and Pavement Design, 3(4), 373-384, 2002.
  • Khan MU, Williams DJ, Ferreira L, Mesbah M. “Developing a new road deterioration model ıncorporating flooding”. Proceedings of the ICE-Transport, 167(5), 322-333, 2014.
  • Pulugurta H, Shao Q, Chou YJ. “Pavement condition prediction using markov process”. Journal of Statistics and Management Systems, 12(5), 853-871, 2009.
  • Lethanh N, Adey BT. “Use of exponential hidden markov models for modelling pavement deterioration”. International Journal of Pavement Engineering, 14(7), 645-654, 2013.
  • Park ES, Smith RE, Freeman TJ, Spiegelman CH. “A bayesian approach for ımproved pavement performance prediction”. Journal of Applied Statistics, 35(11), 1219-1238, 2008.
  • Hong HP, Wang SS. “Stochastic modeling of pavement performance”. International Journal of Pavement Engineering, 4(4), 235-243, 2003.
  • Hassan R, Lin O, Thananjeyan A. “A comparison between three approaches for modelling deterioration of five pavement surfaces”. International Journal of Pavement Engineering, 18(1), 26-35, 2015.
  • Pan NF, Ko CH, Yang MD, Hsu KC. “Pavement performance prediction through fuzzy regression”. Expert Systems with Applications. 38(8), 10010-10017, 2011.
  • Karaşahin M, Terzi S. “Performance model for asphalt concrete pavement based on the fuzzy logic approach”. Transport, 29(1), 18-27, 2014.
  • Attoh-Okine NO. “Analysis of Learning Rate and Momentum Term in Backpropagation Neural Network Algorithm Trained to Predict Pavement Performance”. Advances in Engineering Software, 30(4), 291-302, 1999.
  • Terzi S. “Modeling the pavement serviceability ratio of flexible highway pavements by artificial neural networks”. Construction and Building Materials, 21(3), 590–593, 2007.
  • Terzi S. “Modeling for pavement roughness using the ANFIS approach”. Advances in Engineering Software, 57, 59-64, 2013.
  • Attoh-Okine NO, Mensah S, Nawaiseh M. “A new technique for using multivariate adaptive regression splines (MARS) in pavement roughness prediction”. Proceedings of the Institution of Civil Engineers-Transport, 156(1), 51-55, 2003.
  • Ahmed A, Labi S, Li Z, Shields T. “Aggregate and disaggregate statistical evaluation of the performance-based effectiveness of long-term pavement performance specific pavement study-5 (LTPP SPS-5) flexible pavement rehabilitation treatments”. Structure and Infrastructure Engineering, 9(2), 172-187, 2013.
  • Mubaraki M. “Predicting Pavement Condition Deterioration for the Saudi Inter-Urban Road Network”. GeoHunan International Conference, Changsha, Hunan, China, 3-6 August 2009.
  • Amador-Jiménez LE, Mrawira D. “Reliability-Based initial pavement performance deterioration modelling”. International Journal of Pavement Engineering, 12(2), 177-186, 2011.
  • Fekpe E, Attoh-Okine NO. “Deterioration modelling for lateritic-base flexible pavements”. Construction and Building Materials, 9(3), 159-163, 1995.
  • Bennett C, Petersen W. A Guide to Calibration and Adaptation, Washington, DC, USA, PIARC, 1999.
  • Braga A, Čygas D. “Adaptation of pavement deterioration models to lithuanian automobile roads”. Journal of Civil Engineering and Management, 8(3), 214-220, 2002.
  • Odoki JB, Anyala M, Bunting E. “HDM-4 adaptation for strategic analysis of UK local roads”. Proceedings of the ICE-Transport, 166(2), 65-78, 2013.
  • Martin TC. “Heavy vehicle road wear on sealed unbound granular roads”. Proceedings of the ICE-Transport, 164(1), 13-22, 2011.
  • Jorge D, Ferreira A. “Road network pavement maintenance optimisation using the hdm-4 pavement performance prediction models”. International Journal of Pavement Engineering, 13(1), 39-51, 2012.
  • Chootinan P, Chen A, Horrocks MR, Bolling D. “A multi-year pavement maintenance program using a stochastic simulation-based genetic algorithm approach”. Transportation Research Part A: Policy and Practice, 40(9),725-743, 2006.
  • Chi S, Hwang J, Arellano M, Zhang Z, Murphy M. “Development of network-level project screening methods supporting the 4-year pavement management plan in Texas”. Journal of Management in Engineering, 29(4), 482-494, 2013.
  • Chou JS, Le TS. “Reliability-Based performance simulation for optimized pavement maintenance”. Reliability Engineering & System Safety, 96(10), 1402-1410, 2011.
  • Meneses S, Ferreira A. “Flexible pavement maintenance programming considering the minimisation of maintenance and rehabilitation costs and the maximisation of the residual value of pavements”. International Journal of Pavement Engineering, 16(7), 571-586, 2014.
  • İncegül M, Ergün M. “An ıntegrated graphical user ınterface for pavement deterioration modeling”. Scientific Research and Essay, 6(17), 3649-3656, 2011.
  • Güngör AG, Hacak B, Ünal EN. “Üstyapı yönetim sistemi KGM uygulamaları”. 2. Karayolu Ulusal Kongresi, Ankara, Türkiye, 11-13 Ekim 2011.
  • Park K, Thomas NE, Wayne Lee K. “Applicability of the international roughness ındex as a predictor of asphalt pavement condition”. Journal of Transportation Engineering, 133(12), 706-709, 2007.
There are 42 citations in total.

Details

Subjects Engineering
Journal Section Research Article
Authors

Ufuk Kırbaş This is me 0000-0002-2389-425X

Mustafa Karaşahin 0000-0002-3811-2230

Emine Nazan Ünal This is me 0000-0002-6308-5529

Muhammet Komut This is me 0000-0002-9181-6931

Birol Demir This is me 0000-0003-4827-6551

Kıvılcım Öcal This is me 0000-0003-1733-5184

Publication Date December 15, 2017
Published in Issue Year 2017 Volume: 23 Issue: 6

Cite

APA Kırbaş, U., Karaşahin, M., Ünal, E. N., Komut, M., et al. (2017). Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23(6), 718-725.
AMA Kırbaş U, Karaşahin M, Ünal EN, Komut M, Demir B, Öcal K. Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. December 2017;23(6):718-725.
Chicago Kırbaş, Ufuk, Mustafa Karaşahin, Emine Nazan Ünal, Muhammet Komut, Birol Demir, and Kıvılcım Öcal. “Şehirlerarası Yol ağlarında bitümlü sıcak karışım Kaplamalar için üstyapı Performans Tahmin Modeli geliştirilmesi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23, no. 6 (December 2017): 718-25.
EndNote Kırbaş U, Karaşahin M, Ünal EN, Komut M, Demir B, Öcal K (December 1, 2017) Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23 6 718–725.
IEEE U. Kırbaş, M. Karaşahin, E. N. Ünal, M. Komut, B. Demir, and K. Öcal, “Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 23, no. 6, pp. 718–725, 2017.
ISNAD Kırbaş, Ufuk et al. “Şehirlerarası Yol ağlarında bitümlü sıcak karışım Kaplamalar için üstyapı Performans Tahmin Modeli geliştirilmesi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23/6 (December 2017), 718-725.
JAMA Kırbaş U, Karaşahin M, Ünal EN, Komut M, Demir B, Öcal K. Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2017;23:718–725.
MLA Kırbaş, Ufuk et al. “Şehirlerarası Yol ağlarında bitümlü sıcak karışım Kaplamalar için üstyapı Performans Tahmin Modeli geliştirilmesi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 23, no. 6, 2017, pp. 718-25.
Vancouver Kırbaş U, Karaşahin M, Ünal EN, Komut M, Demir B, Öcal K. Şehirlerarası yol ağlarında bitümlü sıcak karışım kaplamalar için üstyapı performans tahmin modeli geliştirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2017;23(6):718-25.

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