Probabilistic prediction models for crack initiation and progression of spray sealed pavements

References

• AASHTO , 2001. Pavement management guide . Washington, DC: American Association of State Highway and Transportation Officials (AASHTO).
   Google Scholar
• Austroads , 2004. Pavement rehabilitation – a guide to the design of rehabilitation treatments for road pavements . Sydney: Austroads (Austroads Publication No. AP-G78/04).
   Google Scholar
• Byrne, M. and Aguiar, G. , 2010. Impact of climate change on road performance: Updating climate information for Australia . Sydeny: Austroads (Austroads Publication No. AP-R358-10).
   Google Scholar
• Chen, H. and Martin, T. , 2012. dTIMS Asset Management Tool User Documentation, Project No. 001538- Version 1.1.
   Google Scholar
• Choummanivong, L. and Martin, T. , 2013. Probabilistic rad deterioration models development . Sydney: Austroads (Austroads Publication No. AP-T257-13).
   Google Scholar
• Choummanivong, L. and Martin, T. , 2014. Interim rad deterioration cracking model during accelerated deterioration . Sydney: Austroads (Austroads Publication No. AP-T259-14).
   Google Scholar
• Choummanivong, L. and Martin, T. , 2015. Austroads LTPP/LTPPM study – summary report 2013–2014 . Sydeny: Austroads (Austroads Publication No. AP-T288-15).
   Google Scholar
• Christofa, E.M. and Madanat, S.M. , 2010. Development of pavement crack initiation models by combining experimental and field data, 89th annual meeting Transportation Research Board , Washington, DC. Paper No. 10-1096.
   Google Scholar
• Ens, A. , 2012. Development of a flexible framework for deterioration modelling in infrastructure asset management . Dissertation (Master of Applied Science). Department of Civil Engineering, University of Toronto.
   Google Scholar
• Field, A. , 2009. Discovering statistics using SPSS statistics . 3rd ed. London: Sage.
   Google Scholar
• Foley, G.D. , 1999. Pavement condition monitoring in Australasia: The state of the art. Victoria: ARRB Group Limited. Issue Number: ARR 331).
   Google Scholar
• Good, P.I. and Hardin, J.W. , 2003. Common errors in statistics (and How to Avoid Them) . New York, NY: John Wiley & Sons Ltd.10.1002/0471463760
   Google Scholar
• Greene, W. , 2004. Interpreting estimated parameters and measuring individual heterogeneity in random coefficient models . New York, NY: Department of Economics, Stern School of Business, New York University.
   Google Scholar
• Henning, T.F. , 2008. The development of pavement deterioration models on the state highway network of New Zealand . Thesis (PhD). Research Space at Auckland University.
   Google Scholar
• Henning, T.F.P. and Roux, D.C. , 2012. A probabilistic approach for modelling deterioration of asphalt surfaces. Journal of the South African Institution of Civil Engineering , 54 (2), 36–44.
   Web of Science ®Google Scholar
• HLM7 , 2015. HLM7 for Windows [Computer software] by S.W. Raudenbush, A.S. Bryk, & R Congdon, Skokie, IL: Scientific Software International, Inc.
   Google Scholar
• Hodges, J.W. , Rolt, J. , and Jones, T.E. , 1975. The Kenya road transport cost study: Research on road deterioration. Crowthorne: Transport and Road Research Laboratory, Laboratory Report 673.
   Google Scholar
• Hong, F. , 2007. Modeling heterogeneity in transportation infrastructure deterioration: Application to pavement . Thesis (PhD). University of Texas at Austin.
   Google Scholar
• Jameson, G. , 2008. Guide to pavement technology: Part 2: Pavement structural design . Sydney: Austroads (Austroads Publication No. AGPT02-08).
   Google Scholar
• Jameson, G. , 2012. Guide to pavement technology: Part 2: Pavement structural design . Sydney: Austroads (Austroads Publication No. AGPT02-12).
   Google Scholar
• Kadar, P. , et al. , 2015. Addressing uncertainties of performance modelling with stochastic information packages–incorporating uncertainty in performance and budget forecasts. In 9th international conference on managing pavement assets. In: Proceeding of the 9th international conference on managing pavement assets , Washington, DC.
   Google Scholar
• Khraibani, H. , et al. , 2012. Nonlinear mixed-effects model for the evaluation and prediction of pavement deterioration. Journal of Transportation Engineering , 138 (2), 149–156.10.1061/(ASCE)TE.1943-5436.0000257
   Web of Science ®Google Scholar
• Lu, P. , 2011. Modeling pavement performance and preservation . Thesis (PhD), North Dakota State University, Fargo, North Dakota.
   Google Scholar
• Mann, A. 2003. The identification of road sections in Victoria displaying roughness caused by expansive soils . Thesis (MSC), Swinburne University of Technology.
   Google Scholar
• Martin, T.C. , 2008. Predicting sealed granular pavement deterioration at a road network level . Thesis (PhD). Monash University.
   Google Scholar
• Martin, T. and Choummanivong, L. , 2010. Interim network level functional road deterioration models . Sydeny (Austroads Publication No. AP-T158-10).
   Google Scholar
• Martin, T. , Choummanivong, L. , and Toole, T. , 2011. A new pavement deterioration models for sealed low volume roads in Australia. In: Eighth International Conference on Managing Pavement Assets , 15–19 November 2011, Santiago.
   Google Scholar
• Martin, T. and Hoque, Z. , 2006. The identification, classification and causes of pavement under-performance . Canberra: ACT (ARRB Conference, 22nd, 2006).
   Google Scholar
• Martin, T. and Kadar, P. , 2012. The scoping and development of probabilistic road deterioration (RD) models . Austroads: Sydney (Austroads Publication No. AP-T201-12).
   Google Scholar
• Moffatt, M. and Hassan, R. , 2006. Guide to asset management: Part 5e: Cracking . Austroads: Sydney (Austroads Publication No. AGAM05E-06).
   Google Scholar
• NAASRA , 1979. Interim guide to pavement thickness design . Sydney: National Association of Australian State Road Authorities.
   Google Scholar
• Paterson, W.D. , 1987. Road deterioration and maintenance effects: Models for planning and management . Highway Design and Maintenance Standard Series, Baltimore: John Hopkins University Press.
   Google Scholar
• Pearson, D. , 2012. Deterioration and maintenance of pavements . London: ICE Publishing.
   Google Scholar
• Raudenbush, S.W. and Bryk, A.S. , 2002. Hierarchical linear models: Applications and data analysis methods . 2nd ed. Newbury Park: Sage.
   Google Scholar
• Raudenbush, S.W. , et al. , 2011. HLM7 hierarchical linear and nonlinear modeling manual . Lincolnwood, IL: SSI Scientific Software International Inc.
   Google Scholar
• Sharp, K. , 2009. Guide to pavement technology: Part 1: Introduction to pavement technology. Austroads publication No. AGPT01-09 . Sydney: Austroads.
   Google Scholar
• SPSS , 2015. IBM SPSS statistics for Windows, version 22.0. Armonk: IBM Corp.
   Google Scholar
• Thornthwaite, C.W. , 1948. An approach toward a rational classification of climate. Geographical Review (currently published by American Geographical Society) , 38 (1), 55–94.
   Web of Science ®Google Scholar
• Toole, T. , et al. , 2009. Guide to asset management Part 5H: performance modelling , Sydney: Austroads. Austroads Publication No. AGAM05H-09.
   Google Scholar
• VicRoads , 2013. Selection and design of pavements and surfacing, code of practice RC 500.22 . Kew: VicRoads.
   Google Scholar
• Wang, Y. , 2013. Ordinal logistic regression model for predicting AC overlay cracking. Journal of Performance of Constructed Facilities , 27 (3), 346–353.10.1061/(ASCE)CF.1943-5509.0000327
   Web of Science ®Google Scholar
• Yang, J. , 2004. Road crack condition performance modeling using recurrent Markov Chains and artificial neural networks . Thesis (PhD). University of South Florida.
   Google Scholar