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Original Articles

A Bayesian approach for improved pavement performance prediction

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Pages 1219-1238 | Published online: 10 Oct 2008

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Read on this site (4)

Tim Blumenfeld, Arnór Elvarsson, Rade Hajdin, Frank Schiffmann, Grund Christopher & Henning Balck. (2024) A methodology for probabilistic pavement condition forecast based on Bayesian filters. Structure and Infrastructure Engineering 20:1, pages 83-96.
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Angela J. Haddad, George A. Saad & Ghassan R. Chehab. (2023) Kalman filter updating of rutting predictive models in flexible pavements using measured field data. International Journal of Pavement Engineering 24:2.
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Yiching Wu, Yichang (James) Tsai, Georgene M. Geary & Ryan Salameh. (2022) JPCP Slab-Level condition forecasting for slab replacement planning using 3D pavement surface data. International Journal of Pavement Engineering 23:14, pages 4958-4965.
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Elisabete Freitas, Carina Freitas & Ana Cristina Braga. (2014) The analysis of variability of pavement indicators: MPD, SMTD and IRI. A case study of Portugal roads. International Journal of Pavement Engineering 15:4, pages 361-371.
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Articles from other publishers (22)

Babitha Philip & Hamad AlJassmi. (2024) A Bayesian decision support system for optimizing pavement management programs. Heliyon 10:3, pages e25625.
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Qiao Dong, Xueqin Chen & Baoshan Huang. 2024. Data Analysis in Pavement Engineering. Data Analysis in Pavement Engineering 337 345 .
Mohammad Z Bashar & Cristina Torres-Machi. (2023) Machine learning to enhance the management of highway pavements and bridges. Infrastructure Asset Management, pages 1-9.
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Maher Mahmood, Uthayasooriyan Anuraj, Senthan Mathavan & Mujib Rahman. (2023) A unified artificial neural network model for asphalt pavement condition prediction. Proceedings of the Institution of Civil Engineers - Transport 176:1, pages 14-24.
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Davide Lo Presti, Ana Jimenez Del Barco Carrion, Tony Parry, Luis Neves, Elizabeth Keijzer, Bjorn Kalman, Gabriella Buttitta & Konstantinos Mantalovas. (2023) A Framework for Life Cycle Management of Road Pavements in Europe. Transportation Research Procedia 72, pages 1552-1559.
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Qiao Dong, Xueqin Chen, Shi Dong & Fujian Ni. (2022) Data Analysis in Pavement Engineering: An Overview. IEEE Transactions on Intelligent Transportation Systems 23:11, pages 22020-22039.
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Shajib Kumar Guha, Kamal Hossain & Mitchell Lawlor. (2022) An Economic Pavement Management Framework for Extremely Budget- and Resource-Constrained Agencies in Canada. Transportation Research Record: Journal of the Transportation Research Board 2676:8, pages 554-570.
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Aihui Hu, Qiang Bai, Lin Chen, Siyuan Meng, Qihui Li & Zhiman Xu. (2022) A review on empirical methods of pavement performance modeling. Construction and Building Materials 342, pages 127968.
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Arash Hosseini, Ahmed Faheem, Hani Titi & Scot Schwandt. (2022) Deterioration Modeling of Flexible Pavements Based on As-Produced and As-Constructed Properties. Journal of Transportation Engineering, Part B: Pavements 148:2.
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Saviz Moghtadernejad, Gérald Huber, Jürgen Hackl & Bryan T Adey. (2022) Data-driven estimation of deterioration curves: a railway supporting structures case study. Infrastructure Asset Management 9:1, pages 3-17.
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Baoyang Yu, Zongguang Sun & Lin Qi. (2021) Freeze-Thaw Splitting Strength Analysis of PAC Based on the Gray-Markov Model. Advances in Materials Science and Engineering 2021, pages 1-12.
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Mamdouh Mohamed & Dai Q. Tran. (2021) Risk-based inspection for concrete pavement construction using fuzzy sets and bayesian networks. Automation in Construction 128, pages 103761.
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Aswathy RemaAravind Krishna Swamy. (2021) Use of Bayesian Model Averaging to Estimate Model Uncertainty for Predicting Strain in a Four-Layered Flexible Pavement. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering 7:1.
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Sylvester Inkoom, John O. Sobanjo, Eric Chicken, Debajyoti Sinha & Xufeng Niu. (2020) Assessment of Deterioration of Highway Pavement using Bayesian Survival Model. Transportation Research Record: Journal of the Transportation Research Board 2674:6, pages 310-325.
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Maher Mahmood, Mujib Rahman & Senthan Mathavan. (2020) Multi-Types of Flexible Pavement Deterioration Prediction Models. Multi-Types of Flexible Pavement Deterioration Prediction Models.
Maher MahmoodMujib Rahman & Senthan Mathavan. (2019) A multi-input deterioration-prediction model for asphalt road networks. Proceedings of the Institution of Civil Engineers - Transport 172:1, pages 12-23.
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Ufuk Kırbaş & Mustafa Karaşahin. (2016) Performance models for hot mix asphalt pavements in urban roads. Construction and Building Materials 116, pages 281-288.
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Carlos M. Chang, Daniel Saenz & Zheng (Jenny) Li. (2018) Hybrid Modeling Approach for Quantifying Maintenance and Rehabilitation Treatment Effectiveness of Asphalt Pavements. Transportation Research Record: Journal of the Transportation Research Board 2589:1, pages 68-77.
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Megan R. Schlotjes, Michael P. N. Burrow, Harry T. Evdorides & Theunis F. P. Henning. (2015) Using support vector machines to predict the probability of pavement failure. Proceedings of the Institution of Civil Engineers - Transport 168:3, pages 212-222.
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Litao LiuNasir G. Gharaibeh. (2018) Bayesian Model for Predicting the Performance of Pavements Treated with Thin Hot-Mix Asphalt Overlays. Transportation Research Record: Journal of the Transportation Research Board 2431:1, pages 33-41.
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Kiyoshi Kobayashi, Kiyoyuki Kaito & Nam Lethanh. (2012) A statistical deterioration forecasting method using hidden Markov model for infrastructure management. Transportation Research Part B: Methodological 46:4, pages 544-561.
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Filidor Vilca-Labra, Reiko Aoki & Camila Borelli Zeller. (2009) Hypotheses testing for structural calibration model. Statistical Papers 52:3, pages 553-565.
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