Annual Rut Depth Change Prediction Model for National Highway Asphalt Pavements

2021 ◽  
Vol 23 (5) ◽  
pp. 11-19
Author(s):  
Jae Hoon Lee ◽  
Jae Kyu Lim ◽  
Moon Gyu Choi ◽  
Jin Hoon Jeong
Keyword(s):  
Prediction Model ◽  
Asphalt Pavements ◽  
National Highway ◽  
Change Prediction

scholarly journals Development of Macroscopic Cell-Based Logistic Lane Change Prediction Model

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Christina Ng ◽  
Susilawati Susilawati ◽  
Md Abdus Samad Kamal ◽  
Irene Mei Leng Chew
Keyword(s):  
Prediction Model ◽  
Transmission Model ◽  
Lane Change ◽  
Traffic Data ◽  
Cell Transmission Model ◽  
Traffic State ◽  
Proposed Model ◽  
Significant Difference ◽  
The Mean ◽  
Change Prediction

This paper aims at developing a macroscopic cell-based lane change prediction model in a complex urban environment and integrating it into cell transmission model (CTM) to improve the accuracy of macroscopic traffic state estimation. To achieve these objectives, first, based on the observed traffic data, the binary logistic lane change model is developed to formulate the lane change occurrence. Second, the binary logistic lane change is integrated into CTM by refining CTM formulations on how the vehicles in the cell are moving from one cell to another in a longitudinal manner and how cell occupancy is updated after lane change occurrences. The performance of the proposed model is evaluated by comparing the simulated cell occupancy of the proposed model with cell occupancy of US-101 next generation simulation (NGSIM) data. The results indicated no significant difference between the mean of the cell occupancies of the proposed model and the mean of cell occupancies of actual data with a root-mean-square-error (RMSE) of 0.04. Similar results are found when the proposed model was further tested with I80 highway data. It is suggested that the mean of cell occupancies of I80 highway data was not different from the mean of cell occupancies of the proposed model with 0.074 RMSE (0.3 on average).

scholarly journals Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Yanhui Zhong ◽  
Yilong Wang ◽  
Bei Zhang ◽  
Xiaolong Li ◽  
Songtao Li ◽  
...  
Keyword(s):  
Dielectric Properties ◽  
Prediction Model ◽  
Room Temperature ◽  
Asphalt Mixture ◽  
Aggregate Size ◽  
Asphalt Pavements ◽  
Test Results ◽  
Wide Range ◽  
Asphalt Content ◽  
Ground Penetrating

The rapid detection of asphalt content in asphalt mixture is of great significance to the quality evaluation of asphalt pavement. Based on the dielectric properties of an asphalt mixture, the prediction model of asphalt content is deduced theoretically using three types of dielectric models: Lichtenecker-Rother (L-R) model, Rayleigh model, and Bottcher equation. Under the condition of laboratory mixing at room temperature (about 20–25°C), a dielectric test of asphalt mixture is conducted to verify the applicability of the model. The test results indicate that the dielectric constant of the asphalt mixture is inversely proportional to the asphalt content and directly proportional to the aggregate size of the mixture. Among the models, the Rayleigh model has a wide range of applications and exhibits a high accuracy, with an average relative error of only 1.86%. The results provide a theoretical basis for the nondestructive testing of asphalt pavements using ground-penetrating radar.

Prediction of Field Aging Gradient in Asphalt Pavements

2015 ◽  
Vol 2507 (1) ◽  
pp. 19-28 ◽  
Author(s):  
Xue Luo ◽  
Fan Gu ◽  
Robert L. Lytton
Keyword(s):  
Activation Energy ◽  
Prediction Model ◽  
Prediction Models ◽  
Fast Rate ◽  
Chemical Properties ◽  
Asphalt Pavements ◽  
Model Parameters ◽  
Void Content ◽  
Constant Rate ◽  
Rate Period

The aging of asphalt pavements is a key factor that influences pavement performance. Aging can be characterized by laboratory tests and prediction models. Common aging prediction models use the change of physical or chemical properties of asphalt binders based on regression techniques or aging reaction kinetics. The objective of this study was to develop a kinetics-based aging prediction model for the mixture modulus gradient in asphalt pavements to study long-term in-service aging. The proposed model was composed of three submodels for baseline modulus, surface modulus, and aging exponent to define the change of the mixture modulus with pavement depth. The model used kinetic parameters (aging activation energy and preexponential factor) of asphalt mixtures and combined the two reaction rate periods (fast-rate and constant-rate). Laboratory-measured modulus gradients of 29 field cores at different ages were used to determine the model parameters. The laboratory testing condition was converted to the field condition at a given age and corresponding temperature by introducing the rheological activation energy to quantify the temperature dependence of field cores at each age. The end of the fast-rate period or the beginning of the constant-rate period was accurately identified to model these two periods and to determine the associated parameters separately. The results showed that the predictions matched well with the measurements and the calculated model parameters were verified. The proposed aging prediction model took into account the major factors that affect field aging speed of an asphalt pavement, such as the binder type, aggregate type, air void content, pavement depth, aging temperature, and aging time.

scholarly journals An Experimental Investigation on the Repairing Performance and Fatigue Life of Asphalt Pavement Potholes With an Inclined Interface Joint

2021 ◽  
Vol 7 ◽  
Author(s):  
Linyu Li ◽  
Yangquan Huang ◽  
Zhutao Shao ◽  
Dongya Ren
Keyword(s):  
Fatigue Life ◽  
Prediction Model ◽  
Structural Damage ◽  
Experimental Testing ◽  
Asphalt Pavement ◽  
Fatigue Behavior ◽  
Asphalt Pavements ◽  
Joint Interface ◽  
Tack Coat ◽  
Joint Shape

A pothole is a typical structural damage of asphalt pavements that significantly influence the life of asphalt pavements and driving safety. The durability of the existing pit repair methods is generally low. The existing studies in the context of pothole repair mainly focus on the selection and the amount of tack coat materials, nonetheless, very limited studies emphasize the effect of the joint interface shape. This study aims to investigate the influence of the interface joint shape on the service life of pothole repair by experimental testing. The strength and fatigue behavior of the joints were studied and the effectiveness of pothole repairs was evaluated under various conditions, including four temperature levels (5, 10, 15 and 25°C), four strain levels (750 με, 1,000 με, 1,250 με, and 1,500 με) and three loading frequencies (2, 5, and 10 Hz). The optimal interface joint shape was obtained by orthogonal tests. The results indicated that the bond strength and fatigue life of the high viscoelastic emulsified asphalt with an area density of 0.6 kg/m2 in the form of a 30° inclination joint was 473 and 80 times higher than those of traditional pothole repair (i.e., vertical joint form and no tack coat), respectively. Finally, a prediction model was proposed for the interface joint fatigue life considering external parameters through multiple regression analyses. This prediction model can provide a reference for the further study of asphalt pavement pothole repair.

Development of Acoustical Prediction Model for Asphalt Pavements Using Grey System Approach

2010 ◽  
Vol 11 (3) ◽  
pp. 783-805
Author(s):  
Chia-Ming Wu ◽  
Cheng-chao Lee ◽  
Jia-Chong Lee ◽  
Der-Hsien Shen
Keyword(s):  
Prediction Model ◽  
System Approach ◽  
Asphalt Pavements ◽  
Grey System

A Bayesian inference based adaptive lane change prediction model

2021 ◽  
Vol 132 ◽  
pp. 103363
Author(s):  
Jinghua Wang ◽  
Zhao Zhang ◽  
Guangquan Lu
Keyword(s):  
Bayesian Inference ◽  
Prediction Model ◽  
Lane Change ◽  
Change Prediction

scholarly journals The Topography Change Prediction Model that considered a Flow caused by Wind in the Niigata West Coast

2008 ◽  
Vol 55 ◽  
pp. 586-590
Author(s):  
Hiroshi YOSHINAGA ◽  
Hideki YOSHIDA ◽  
Tadashi YOSHIDA ◽  
Tomonori IBE ◽  
Keiji KUROKI
Keyword(s):  
Prediction Model ◽  
West Coast ◽  
Change Prediction
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