Evaluation of 3D Automated Systems for the Measurement of Pavement Surface Cracking

Serigos, Pedro A.; Prozzi, Jorge A; Smit, André de Fortier; Murphy, Michael R.

doi:10.1061/(asce)te.1943-5436.0000841

Cited by 21 publications

(9 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Serigos et al [28] made an independent evaluation of the accuracy and precision of three different laser-based pavement crack detection (two of them based on the same hardware but different proprietary algorithms). These methods provide acceptable results, but due to the capture method, it is difficult to compare the method proposed in this article with Serigos et al work.…”

Section: Related Workmentioning

confidence: 99%

Efficient pavement crack detection and classification

Cubero-Fernandez

Rodriguez-Lozano

Villatoro

et al. 2017

J Image Video Proc.

159

104

View full text Add to dashboard Cite

Each year, millions of dollars are invested on road maintenance and reparation all over the world. In order to minimize costs, one of the main aspects is the early detection of those flaws. Different types of cracks require different types of repairs; therefore, not only a crack detection is required but a crack type classification. Also, the earlier the crack is detected, the cheaper the reparation is. Once the images are captured, several processes are applied in order to extract the main characteristics for emphasizing the cracks (logarithmic transformation, bilateral filter, Canny algorithm, and a morphological filter). After image preprocessing, a decision tree heuristic algorithm is applied to finally classify the image. This work obtained an average of 88% of success detecting cracks and an 80% of success detecting the type of the crack. It could be implemented in a vehicle traveling as fast as 130 kmh or 81 mph.

show abstract

Section: Related Workmentioning

confidence: 99%

Efficient pavement crack detection and classification

Cubero-Fernandez

Rodriguez-Lozano

Villatoro

et al. 2017

J Image Video Proc.

159

104

View full text Add to dashboard Cite

show abstract

“…The automated principle is a measure of the distance from the sensors to pavement surface by taking pictures which are then analyzed using computers. Using automated methods eliminates traffic interruptions and obtains several profiles transverse depending on the systems used (16). In the U.S.A. and Canadian agencies, there are about 46, out of 56, used automated methods to collect rut depth (17).…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling Road Pavement Rutting Using Artificial Neural Network and Conventional Measurements

Shatnawi

Obaidat

Al-Sharideah

2022

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Rutting leads hydroplaning, accidents, poor riding quality, and significant maintenance costs. This study assists the development of statistical and Artificial pavement rutting models. The proposed methodology is reliable, time-saving, cost-saving, and comfortable. The suggested technique to anticipate rutting considers traffic volumes, pavement, and geometrical parameters such as lane and shoulder widths. This research modeled 33 main highways' ruts. Most of these roads have serious de-stressing problems with rutted pavement. The developed rutting prediction models demonstrated a medium to high correlation between rut depth and independent variables including annual average daily traffic, truck fleet percentage, pavement thickness, and number of lanes. The correlation coefficients such as R2 were found to be moderate for most of the developed models. The linear models of rutting prediction were statistically significant, with R2 values averaging around 66%, whereas the logistic regression model was the best developed rutting model, with an R2 value of 67%, when all variables, including traffic, pavement, and geometry, were considered. Nonlinear models with an R2 value of 57% were used to get similar findings. The artificial neural network (ANN) has been used in this study to model rut depth with same independent variables and gave higher results with R2 value of 82%. The findings showed that an ANN outperformed regression modeling in predicting the depth of a rut.

show abstract

“…Further, affected by the natural environment and worn by moving vehicles, asphalt pavement is prone to age with use. As a result, its water stability and ground temperature deformation capacity are weakened, which can lead to pavement damage, defects, and rutting disease that affect the quality of the pavement structure and its service life further [ 4 – 6 ]. SMA asphalt pavement has good durability and water stability, and performs well at high and low temperatures.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of graphene modified asphalt and pavement performance of SMA mixture

et al. 2022

View full text Add to dashboard Cite

The graphene modified asphalt used in this study was prepared based on a highway project in Gansu Province. In this paper, the high temperature rutting resistance, low temperature cracking resistance, and water stability of SMA-13 asphalt mixture with asphalt (AH-70), SBS modified asphalt and graphene rubber composite modified asphalt were tested and analyzed comparatively by the rutting test, Schellenberg binder drainage test, Cantabro test, freeze-thaw splitting test, and beam bending test. The results showed that the graphene modifier improved the asphalt’s ductility and softening point significantly, and 0.4g graphene content was the threshold and its corresponding mixture performance index. In the other tests under the same conditions, the high temperature and water stability of SMA-13 mixtures of graphene rubber modified asphalt were the best, followed by SBS modified asphalt mixture, and matrix asphalt mixture. Compared with wood fiber, graphene modifier had no significant effect on SMA-13 mixtures’ low temperature performance. The use of graphene modifiers can enhance the adhesion between asphalt and aggregate and its asphalt has good consistency and viscosity. When compared with matrix asphalt and SBS modified SMA-13 mixtures, the water and high temperature stability of graphene modified asphalt mixture is better.

show abstract

Evaluation of 3D Automated Systems for the Measurement of Pavement Surface Cracking

Cited by 21 publications

References 6 publications

Efficient pavement crack detection and classification

Efficient pavement crack detection and classification

Modeling Road Pavement Rutting Using Artificial Neural Network and Conventional Measurements

Performance analysis of graphene modified asphalt and pavement performance of SMA mixture

Contact Info

Product

Resources

About