Road Pavement Condition Index Deterioration Model for Network-Level Analysis of National Road Network Based on Pavement Condition Scanning Data
DOI:
https://doi.org/10.7250/bjrbe.2023-18.609Keywords:
deterioration, IRI, pavement performance, pavement condition index, PCI, panel data analysis, regression analysis, road condition surveyAbstract
Surveying the condition of the pavement is one of the most important processes in managing the road network. The information collected during these surveys allows for the calculation of the Pavement Condition Index, which is a derivative cumulative qualitative indicator that evaluates various pavement characteristics and defects. Deterioration modelling of these measured indicators and calculated indices is a critical element and its most accurate prediction brings the process of pavement management closer to a higher quality process by more efficiently allocating funds and repair work. Many different models – both extremely complex and simple – are used in the world to simulate the condition of individual pavement indicators. However, these models are developed based on the data of a certain country or region and are not suitable in another country due to different requirements for pavement structures and other reasons. In Lithuania, measurements of the quality indicators of road surfaces with new generation survey equipment have been carried out recently but the information stored in the databases about road sections is minimal, and it becomes difficult to adapt the models applied abroad due to the missing information. The aim of this study is to create pavement condition index prediction models by evaluating such quantitative and qualitative indicators as traffic loads, road surface unevenness, type of repair, pavement age, climatic zones, and pavement construction classes.
References
AASHTO. (1990). AASHTO guidelines for pavement management systems. American Association of State Highways and Transportation Officials, Washington DC.
AASHTO. (2011). Transportation asset management guide: A focus on implementation. American Association of State Highway and Transportation Officials, Washington, DC.
Braga, A. (2005). Dangų degradacijos modeliai ir jų taikymas Lietuvos automobilių keliams (Models of Pavement Deterioration and their Adaptation to Lithuanian Automobile Roads). https://vb.vgtu.lt/object/elaba:2028088/
Busch, C., & Scar A. (2010). NordFoU PPM – Identification and selection of network level analysis identification and selection of pavement performance models. https://www.researchgate.net/publication/282867666_NordFoU_PPM_-_Identification_and_Selection_of_Pavement_Performance_Models
Dabous, S. A., Al-Khayyat, G., & Feroz, S. (2020). Utility-based road maintenance prioritization method using pavement overall condition rating. Baltic Journal of Road and Bridge Engineering, 15(1), 126–146. https://doi.org/10.7250/bjrbe.2020-15.464
Deix, S., Alten, K., & Weninger-Vycudil, A. (2012). Procedures for cross asset management optimisation. Procedia – Social and Behavioral Sciences, 48, 2022–2028. https://doi.org/10.1016/j.sbspro.2012.06.1175
Elhadidy, A. A., El-Badawy, S. M., & Elbeltagi, E. E. (2019). A simplified pavement condition index regression model for pavement evaluation. International Journal of Pavement Engineering, 22(5), 643–652. https://doi.org/10.1080/10298436.2019.1633579
Erlingsson, S. (2010). Modelling of rutting performance – Comparison with LTPP road sections. NordFoU PPM, Nordic Cooperation Program.
Gharieb, M., Nishikawa, T., Nakamura, S., & Thepvongsa, K. (2022). Modeling of pavement roughness utilizing artificial neural network approach for Laos national road network. Journal of Civil Engineering and Management, 28(4), 261–277. https://doi.org/10.3846/jcem.2022.15851
Gordon, M., Sharp, K., & Martin, T. (2018). Guide to asset management-processes part 3: scope of asset management (Report No. AGAM03-18). https://trid.trb.org/view/1527943
Jurkevičius, M., Puodžiukas, V., & Laurinavičius, A. (2020). Implementation of road performance calculation models used in strategic planning systems for Lithuania conditions. Baltic Journal of Road and Bridge Engineering, 15(3), 146–156. https://doi.org/10.7250/bjrbe.2020-15.489
Karimzadeh, A., & Shoghli, O. (2020). Predictive analytics for roadway maintenance: A review of current models, challenges, and opportunities. Civil Engineering Journal, 6(3), 602–625. https://doi.org/10.28991/cej-2020-03091495
Kleizienė, R., Vaitkus, A., Židanavičiūtė, J., & Marcinkevičius, E. (2017). Classification of surface temperature for the flexible pavement design. International Conference “Environmental Engineering”. https://doi.org/10.3846/enviro.2017.139
I., Vaitkus, A., & Kleizienė, R. (2020). Comparison of pavement performance models for urban road management system. Baltic Journal of Road and Bridge Engineering, 15(3), 111–129. https://doi.org/10.7250/bjrbe.2020-15.487
Kulkarni, R. B., & Miller, R. W. (2003). Pavement management systems: Past, present, and future. Transportation Research Record, 1853(1), 65–71. https://doi.org/10.3141/1853-08
LAKD. (2018). Valstybinės reikšmės kelių dangos būklės vertinimo tvarkos aprašas. Lietuvos automobilių kelių direkcija.
Lin, D. J., & Madanat, S. (2002). Development of pavement deterioration models by combining experimental and field data sets. Applications of Advanced Technologies in Transportation, 2002, 529–536. https://doi.org/10.1061/40632(245)67
Litzka, J., Leben, B., La Torre, F., Weninger-Vycudil, A., Antunes, M. de L., Kokot, D., Mladenovic, G., Brittain, S., & Viner, H. (2008). The way forward for pavement performance indicators in Europe (Final Report COST 354). http://cost354.zag.si/fileadmin/cost354/1fr/COST354_FinalReport_05062008.pdf
Madanat, S. (1993). Optimal infrastructure management decisions under uncertainty. Transportation Research Part C, 1(1), 77–88. https://doi.org/10.1016/0968-090X(93)90021-7
Okine, A., & Adarkwa, O. (2013). Pavement condition surveys – overview of current practices. Delaware Center for Transportation, University of Delaware. https://cpb-us-w2.wpmucdn.com/sites.udel.edu/dist/1/1139/files/2013/10/Rpt-245-Pavement-Condition-Okine-DCTR422232-1pzk0uz.pdf
Paterson, W. D. O. (1990). Road deterioration and maintenance effects. Models for planning and management. Transportation Research Part A: General, 24(2). https://doi.org/10.1016/0191-2607(90)90027-4
Peraka, N. S. P., & Biligiri, K. P. (2020). Pavement asset management systems and technologies: A review. Automation in Construction, 119, Article 103336. https://doi.org/10.1016/j.autcon.2020.103336
Pierce, L. M., & Weitzel, N. D. (Eds.). (2019). Automated pavement condition surveys. National Academies of Sciences, Engineering, and Medicine. https://doi.org/10.17226/25513
Sjögren, L. (2015). History of road profile measurements and current standards in road surface characteristics. ERPUG, Budapest, Hungary. http://www.erpug.org/media/files/forelasningar_2015/1_ERPUG_2015_Leif_VTI.pdf
Vaitkus, A., Gražulyte, J., Skrodenis, E., & Kravcovas, I. (2016). Design of frost resistant pavement structure based on road weather stations (RWSs) data. Sustainability (Switzerland), 8(12), Article 1328. https://doi.org/10.3390/su8121328
Vaitkus, A., Kleizienė, R., & Karbočius, M. (2021). Viastructura – A new way of pavement structure design. IOP Conference Series: Materials Science and Engineering, 1202(1), Article 012018. https://doi.org/10.1088/1757-899x/1202/1/012018
VĮ Lietuvos automobilių kelių direkcija (LAKD). (2019). Automobilių kelių standartizuotų dangų konstrukcijų projektavimo taisyklės KPT SDK 19.
Wadalkar, S. S., Lad, R. K., & Jain, R. K. (2018). Study of pavement performance indicators: RII Approach. Indian Journal of Science and Technology, 11(22), 1–4. https://doi.org/10.17485/ijst/2018/v11i22/121101
Zofka, A., Josen, R., Paliukaite, M., Vaitkus, A., Mechowski, T., & Maliszewski, M. (2014). Elements of pavement management system: Case study. Baltic Journal of Road and Bridge Engineering, 9(1), 1–9. https://doi.org/10.3846/bjrbe.2014.01
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