Pavement Performance Prediction through Fuzzy Logic Using Marine Corps Air Station Cherry Point, North Carolina Measurements

Author(s):  
S. Terzi ◽  
Ş. Sargın ◽  
M. Saltan
Author(s):  
Paul K. Chan ◽  
Mary C. Oppermann ◽  
Shie-Shin Wu

Development efforts in pavement performance prediction by the North Carolina Department of Transportation are described. Research into other states’ approaches was also conducted. The initial idea was to use family curves. However, because of a lack of data in key areas, it was decided to use an individual section’s pavement condition rating (PCR) data for performance prediction. The process of selection and justification of a functional form for curve fitting is detailed. An adaptive scheme to accommodate a realistic PCR history containing cycles of decline and improvement in the ratings is detailed. Abnormal sections that did not fit the models developed for individual sections were identified. These were either ( a) section with too few datum points for modeling or ( b) sections in which the last few ratings leveled out, resulting in a prediction of an unreasonably long life span. The development of family curves and their application in the processing of abnormal sections are also discussed. The developed models were then evaluated by comparing the predicted rating with the actual rating.


Author(s):  
Ram B. Kulkarni ◽  
Richard W. Miller

The progress made over the past three decades in the key elements of pavement management systems was evaluated, and the significant improvements expected over the next 10 years were projected. Eight specific elements of a pavement management system were addressed: functions, data collection and management, pavement performance prediction, economic analysis, priority evaluation, optimization, institutional issues, and information technology. Among the significant improvements expected in pavement management systems in the next decade are improved linkage among, and better access to, databases; systematic updating of pavement performance prediction models by using data from ongoing pavement condition surveys; seamless integration of the multiple management systems of interest to a transportation organization; greater use of geographic information and Global Positioning Systems; increasing use of imaging and scanning and automatic interpretation technologies; and extensive use of formal optimization methods to make the best use of limited resources.


2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xuancang Wang ◽  
Jing Zhao ◽  
Qiqi Li ◽  
Naren Fang ◽  
Peicheng Wang ◽  
...  

Pavement performance prediction is a crucial issue in big data maintenance. This paper develops a hybrid grey relation analysis (GRA) and support vector machine regression (SVR) technique to predict pavement performance. The prediction model can solve the shortcomings of the traditional model including a single consideration factor, a short prediction period, and easy overfitting. GAR is employed in selecting the main factors affecting the performance of asphalt pavement. The SVR is performed to predict the performance. Finally, the data collected from the weather station installed on Guangyun Expressway were adopted to verify the validity of the GRA-SVR model. Meanwhile, the contrast with the grey model (GM (1, 1)), genetic algorithm optimization BP[[parms resize(1),pos(50,50),size(200,200),bgcol(156)]]081%, −0.823%, 1.270%, and −4.569%, respectively. The study concluded that the nonlinear and multivariate prediction model established by GRA-SVR has higher precision and operability, which can be used in long-period pavement performance prediction.


Author(s):  
A. Samy Noureldin ◽  
Essam Sharaf ◽  
Abdulrahim Arafah ◽  
Faisal Al-Sugair

Explicit applications of reliability in pavement engineering have been of interest to pavement engineers for the last 10 years. Variabilities in parameters affecting pavement design performance result in variability in pavement performance prediction and thus affect the reliability of how long the pavement will last. Rational quantification of those variabilities is essential for incorporating reliability and selecting the proper factors of safety in the pavement design performance process. The prevailing methodology in Saudi Arabia of quantifying the variability in pavement performance due to the variabilities of the parameters affecting that performance is demonstrated. Factors of safety for flexible pavement design at various reliability levels and based on those prevailing variabilities are presented. These factors of safety are recommended for flexible pavement design in Saudi Arabia.


Author(s):  
Stephen B. Seeds ◽  
Rudramunniyappa Basavaraju ◽  
Jon A. Epps ◽  
Richard M. Weed

The primary objective of the FHWA-sponsored WesTrack project is to further the development of performance-related specifications for hotmix asphalt construction. This objective is being achieved, in part, through the accelerated loading of a full-scale test track facility in northern Nevada. Twenty-six hot-mix asphalt test sections constructed to meet the criteria set forth in a statistically based experiment design are providing performance data that will be used to improve existing (or develop new) pavement performance prediction relationships that better account for the effects that “off-target” values of asphalt content, air-void content, and aggregate gradation have on such distress factors as fatigue cracking, permanent deformation, roughness, raveling, and tirepavement friction. The concept of the planned new performance-related specification and how it will incorporate the modified pavement performance prediction models are described. The current plan for assessing contractor pay adjustments (i.e., penalties and bonuses) based on data collected from the as-constructed pavement is also discussed.


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