{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T21:49:36Z","timestamp":1778622576470,"version":"3.51.4"},"reference-count":62,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T00:00:00Z","timestamp":1620345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["PD\/BD\/113721\/2015"],"award-info":[{"award-number":["PD\/BD\/113721\/2015"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sustainability"],"abstract":"<jats:p>Road transportation has always been inherent in developing societies, impacting between 10\u201320% of Gross Domestic Product (GDP). It is responsible for personal mobility (access to services, goods, and leisure), and that is why world economies rely upon the efficient and safe functioning of transportation facilities. Road maintenance is vital since the need for maintenance increases as road infrastructure ages and is based on sustainability, meaning that spending money now saves much more in the future. Furthermore, road maintenance plays a significant role in road safety. However, pavement management is a challenging task because available budgets are limited. Road agencies need to set programming plans for the short term and the long term to select and schedule maintenance and rehabilitation operations. Pavement performance prediction models (PPPMs) are a crucial element in pavement management systems (PMSs), providing the prediction of distresses and, therefore, allowing active and efficient management. This work aims to review the modeling techniques that are commonly used in the development of these models. The pavement deterioration process is stochastic by nature. It requires complex deterministic or probabilistic modeling techniques, which will be presented here, as well as the advantages and disadvantages of each of them. Finally, conclusions will be drawn, and some guidelines to support the development of PPPMs will be proposed.<\/jats:p>","DOI":"10.3390\/su13095248","type":"journal-article","created":{"date-parts":[[2021,5,7]],"date-time":"2021-05-07T22:36:24Z","timestamp":1620426984000},"page":"5248","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":123,"title":["Review on Machine Learning Techniques for Developing Pavement Performance Prediction Models"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0228-7629","authenticated-orcid":false,"given":"Rita","family":"Justo-Silva","sequence":"first","affiliation":[{"name":"Research Centre for Territory, Transports and Environment, Department of Civil Engineering, University of Coimbra, 3030-788 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1681-0759","authenticated-orcid":false,"given":"Adelino","family":"Ferreira","sequence":"additional","affiliation":[{"name":"Research Centre for Territory, Transports and Environment, Department of Civil Engineering, University of Coimbra, 3030-788 Coimbra, Portugal"}]},{"given":"Gerardo","family":"Flintsch","sequence":"additional","affiliation":[{"name":"Center for Sustainable Transportation Infrastructure, Virginia Tech Transportation Institute (VTTI), Department of Civil and Environmental Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0131, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,7]]},"reference":[{"key":"ref_1","unstructured":"Branco, F., Pereira, P., and Picado-Santos, L. (2016). Pavimentos Rodovi\u00e1rios, Edi\u00e7\u00f5es Almedina."},{"key":"ref_2","unstructured":"Yang, J., Lu, J.J., and Gunaratne, M. (2003). Application of Neural Network Models for Forecasting of Pavement Crack Index and Pavement Condition Rating, University of South Florida. Technical Report."},{"key":"ref_3","unstructured":"Odoki, J.B., and Kerali, H.R. (2013). HDM-4 Volume 4: Analytical Framework and Model Descriptions, World Road Association (PIARC)."},{"key":"ref_4","unstructured":"OCDE (1991). Essai OCDE en Vraie Grandeur des Superstructures Routi\u00e8res. Recherche en Mati\u00e8re de Routes et de Transports Routiers, Organisation de Coop\u00e9ration et de D\u00e9veloppement \u00c9conomiques (OCDE)."},{"key":"ref_5","unstructured":"COST324 (1997). Long Term Performance of Road Pavements, European Commission. Final Report of the Action."},{"key":"ref_6","unstructured":"(1998). Pavement Deterioration Models: Deliverable D4-RO 96-SC.404, European Commission. Technical Report."},{"key":"ref_7","unstructured":"MathWorks (2019, July 18). Introducing Machine Learning. Available online: https:\/\/www.mathworks.com\/content\/dam\/mathworks\/ebook\/gated\/machineLearning-ebook.pdf."},{"key":"ref_8","unstructured":"Kelleher, J.D., Mac Namee, B., and D\u2019Arcy, A. (2015). Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies, MIT Press."},{"key":"ref_9","unstructured":"AASHTO (2012). Pavement Management Guide, American Association of State Highway and Transportation Officials. [2nd ed.]. Technical Report."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1177\/0361198196152400114","article-title":"Deterioration prediction modeling of Virginia\u2019s interstate highway system","volume":"1524","author":"Sadek","year":"1996","journal-title":"Transp. Res. Rec."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1080\/10298430802169390","article-title":"Effect of design and site factors on fatigue cracking of new flexible pavements in the LTPP SPS-1 experiment","volume":"10","author":"Haider","year":"2009","journal-title":"Int. J. Pavement Eng."},{"key":"ref_12","first-page":"979","article-title":"Comparative analysis of fuzzy decision tree and logistic regression methods for pavement treatment prediction","volume":"5","author":"Kaur","year":"2008","journal-title":"WSEAS Trans. Inf. Sci. Appl."},{"key":"ref_13","unstructured":"Henning, T.F.P., Costello, S.B., and Watson, T.G. (2006). A Review of the HDM\/dTIMS Pavement Models Based on Calibration Site Data, Land Transport New Zealand."},{"key":"ref_14","unstructured":"Li, Z. (2005). A Probabilistic and Adaptive Approach to Modeling Performance of Pavement Infrastructure. [Ph.D. Thesis, University of Texas]."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1061\/(ASCE)0733-947X(1993)119:1(43)","article-title":"Infrastructure management under uncertainty: Latent performance approach","volume":"119","author":"Humplick","year":"1993","journal-title":"J. Transp. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1061\/(ASCE)1076-0342(1995)1:1(33)","article-title":"Modeling infrastructure performance and user costs","volume":"1","author":"Gopinath","year":"1995","journal-title":"J. Infrastruct. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.trc.2006.11.004","article-title":"Estimation of infrastructure performance models using state-space specifications of time series models","volume":"15","author":"Chu","year":"2007","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Durbin, J., and Koopman, S.J. (2012). Time Series Analysis by State Space Methods, Oxford University Press.","DOI":"10.1093\/acprof:oso\/9780199641178.001.0001"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.trb.2006.08.002","article-title":"A time series analysis framework for transportation infrastructure management","volume":"41","year":"2007","journal-title":"Transp. Res. Part B Methodol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.sbspro.2012.06.984","article-title":"Modeling the road degradation process: Nonlinear mixed effects models for correlation and heteroscedasticity of pavement longitudinal data","volume":"48","author":"Lorino","year":"2012","journal-title":"Procedia Soc. Behav. Sci."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"963","DOI":"10.2307\/2529876","article-title":"Random-effects models for longitudinal data","volume":"38","author":"Laird","year":"1982","journal-title":"Biometrics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/00031305.1985.10479402","article-title":"Linear models for analysis of longitudinal studies","volume":"39","author":"Ware","year":"1985","journal-title":"Am. Stat."},{"key":"ref_23","unstructured":"Diggle, P.J., Liang, K.L., and Zeger, S.L. (1994). Analysis of Longitudinal Data, Oxford University Press."},{"key":"ref_24","unstructured":"Davidian, M., and Giltinan, D.M. (1995). Nonlinear Models for Repeated Measurement Data, Chapman and Hall."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Vonesh, E., and Chinchilli, V.M. (1996). Linear and Nonlinear Models for the Analysis of Repeated Measurements, CRC Press.","DOI":"10.1201\/9781482293272"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"70","DOI":"10.3141\/1764-08","article-title":"Statistical model of pavement rutting in asphalt concrete mixes","volume":"1764","author":"Madanat","year":"2001","journal-title":"Transp. Res. Rec."},{"key":"ref_27","first-page":"188","article-title":"Prediction of remaining service life of pavement using an optimized support vector machine (case study of Semnan\u2013Firuzkuh road)","volume":"13","author":"Karballaeezadeh","year":"2019","journal-title":"Eng. Appl. Comput. Fluid Mech."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"135","DOI":"10.3141\/2589-15","article-title":"Prediction of pavement performance: Application of support vector regression with different kernels","volume":"2589","author":"Ziari","year":"2016","journal-title":"Transp. Res. Rec."},{"key":"ref_29","unstructured":"Wasserman, P.D. (1989). Neural Computing, Van Nostrand Reinhold."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"89","DOI":"10.3141\/1592-11","article-title":"Roughness level probability prediction using artificial neural networks","volume":"1592","author":"Huang","year":"1997","journal-title":"Transp. Res. Rec."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"26","DOI":"10.3141\/1592-04","article-title":"Expert project recommendation procedure for Arizona Department of Transportation\u2019s pavement management system","volume":"1592","author":"Flintsch","year":"1997","journal-title":"Transp. Res. Rec."},{"key":"ref_32","unstructured":"Bosurgi, G., Trifir\u00f2, F., and Xilbilia, M.G. (2007, January 12\u201314). Artificial neural network for predicting road pavement conditions. Proceedings of the 4th International SIIV Congress, Palermo, Italy."},{"key":"ref_33","first-page":"635","article-title":"Incremental nonlinear model for predicting pavement serviceability","volume":"129","author":"Prozzi","year":"2003","journal-title":"J. Infrastruct. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1061\/(ASCE)0733-947X(2005)131:11(861)","article-title":"Use of recurrent Markov chains for modeling the crack performance of flexible pavements","volume":"131","author":"Yang","year":"2005","journal-title":"J. Transp. Eng."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Kononenko, I., and Kukar, M. (2007). Machine Learning and Data Mining, Horwood Publishing.","DOI":"10.1533\/9780857099440"},{"key":"ref_36","unstructured":"Smith, W., Finn, F., Kulkarni, R., Saraf, C., and Nair, K. (1979). NCHRP Report 213: Bayesian methodology for verifying recommendations to minimize asphalt pavement distress. Transportation Research Board, National Research Council, Transportation Research Board."},{"key":"ref_37","unstructured":"Haper, W.V., and Majidzadeh, K. (1991, January 15). Utilization of expert opinion in the two pavement management systems. Proceedings of the 70th Annual Meeting of the Transportation Research Board, Washington, DC, USA."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1177\/0361198196152400119","article-title":"Pavement performance modeling using Canadian strategic highway research program bayesian statistical methodology","volume":"1524","author":"Hajek","year":"1996","journal-title":"Transp. Res. Rec."},{"key":"ref_39","unstructured":"Pereira, P.A., and Barbosa, N. (1998). Sistema de Gest\u00e3o da Conserva\u00e7\u00e3o\u2014Manual de Utiliza\u00e7\u00e3o do PRISM, Universidade do Minho."},{"key":"ref_40","unstructured":"Hong, F., and Prozzi, J.A. (2005, January 6). Updating pavement deterioration models using the Bayesian principles and simulation techniques. Proceedings of the 1st Annual Inter-University Symposium on Infrastructure Management, Waterloo, ON, Canada."},{"key":"ref_41","first-page":"28","article-title":"Bayesian regression in pavement deterioration modeling: Revisiting the AASHO road test rut depth model","volume":"14","author":"Mrawira","year":"2012","journal-title":"Infraestruct. Vial"},{"key":"ref_42","unstructured":"Litao, L. (2013). A Methodology for Developing Performance-related Specifications for Pavement Preservation Treatments. [Ph.D. Thesis, Texas A&M Transportation Institute]."},{"key":"ref_43","first-page":"49","article-title":"Arizona Pavement Management System: Phase 2, Verification of performance prediction models and development of data base","volume":"846","author":"Way","year":"1982","journal-title":"Transp. Res. Rec."},{"key":"ref_44","first-page":"12","article-title":"Pavement performance prediction model using the Markov process","volume":"1123","author":"Butt","year":"1987","journal-title":"Transp. Res. Rec."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1177\/0361198196152400124","article-title":"Reliability-based processing of Markov chains for modeling pavement network deterioration","volume":"1524","author":"Li","year":"1996","journal-title":"Transp. Res. Rec."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"48","DOI":"10.3141\/1990-06","article-title":"Dynamic probabilistic approach for long-term pavement restoration program with added user cost","volume":"1990","author":"Abaza","year":"2007","journal-title":"Transp. Res. Rec."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Abaza, K., and Murad, M. (2009). Predicting flexible pavement remaining strength and overlay design thickness with stochastic modeling. Transp. Res. Rec. J. Transp. Res. Board.","DOI":"10.3141\/2094-07"},{"key":"ref_48","first-page":"663","article-title":"Stochastic approach for design of flexible pavement","volume":"12","author":"Abaza","year":"2011","journal-title":"Road Mater. Pavement Des."},{"key":"ref_49","unstructured":"Ferreira, A., Picado-Santos, L., and Antunes, A. (1999, January 13\u201315). Pavement performance modelling: State of the art. Proceedings of the Seventh International Conference on Civil and Structural Engineering Computing, Egmond aan Zee, The Netherlands."},{"key":"ref_50","first-page":"254","article-title":"Determining investment priorities for urban pavement improvements","volume":"45","author":"Karan","year":"1976","journal-title":"Proc. Assoc. Asph. Paving Technol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1287\/inte.12.6.5","article-title":"A Statewide pavement management system","volume":"12","author":"Golabi","year":"1982","journal-title":"Interfaces"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1061\/(ASCE)0733-947X(1994)120:3(358)","article-title":"Probabilistic behavior of pavements","volume":"120","author":"Wang","year":"1994","journal-title":"J. Transp. Eng."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/10298430290030603","article-title":"A segment-linked optimization model for deterministic pavement management systems","volume":"3","author":"Ferreira","year":"2002","journal-title":"Int. J. Pavement Eng."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1061\/(ASCE)1076-0342(2002)8:4(139)","article-title":"Computation of infrastructure transition probabilities using stochastic models","volume":"8","author":"Mishalani","year":"2002","journal-title":"J. Infrastruct. Syst."},{"key":"ref_55","unstructured":"Shahin, M.Y. (2005). Pavement Management for Airports, Roads, and Parking Lots, Springer."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1061\/(ASCE)0733-947X(2006)132:2(141)","article-title":"Derivation of transition probability matrices for pavement deterioration","volume":"132","author":"Costello","year":"2006","journal-title":"J. Transp. Eng."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1061\/(ASCE)1076-0342(1995)1:2(120)","article-title":"Estimation of infrastructure transition probabilities from condition rating data","volume":"1","author":"Madanat","year":"1995","journal-title":"J. Infrastruct. Syst."},{"key":"ref_58","first-page":"853","article-title":"Pavement condition prediction using Markov process","volume":"12","author":"Pulugurta","year":"2009","journal-title":"J. Stat. Manag. Syst."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/1029843031000087464","article-title":"An optimum design approach for flexible pavement","volume":"4","author":"Abaza","year":"2003","journal-title":"Int. J. Pavement Eng."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1061\/(ASCE)0733-947X(2005)131:2(149)","article-title":"Performance-based models for flexible pavement structural overlay design","volume":"131","author":"Abaza","year":"2005","journal-title":"J. Transp. Eng."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1080\/10298430410001672246","article-title":"Stochastic modeling of pavement performance","volume":"4","author":"Hong","year":"2003","journal-title":"Int. J. Pavement Eng."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1080\/0740817X.2014.959672","article-title":"Predictive analytics using a nonhomogeneous semi-Markov model and inspection data","volume":"47","author":"Moghaddass","year":"2015","journal-title":"IIE Trans."}],"container-title":["Sustainability"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2071-1050\/13\/9\/5248\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:58:06Z","timestamp":1760162286000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2071-1050\/13\/9\/5248"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,7]]},"references-count":62,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["su13095248"],"URL":"https:\/\/doi.org\/10.3390\/su13095248","relation":{},"ISSN":["2071-1050"],"issn-type":[{"value":"2071-1050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,7]]}}}