01593950

Monograph

http://www.trb.org/Main/Blurbs/173944.aspx

The objective of this study is to develop successful and effective raveling detection, classification, and measurement algorithms using three-dimensional (3D) pavement data and macro-texture analysis, and to comprehensively validate these methods using large-scale, real-world data. The developed algorithms, using 3D pavement data and the accompanying two-dimensional (2D) intensity data, include the following five components: 1) data pre-processing to remove data outliers, detect pavement markings and edge drop-off, and extract the candidate pavement portion for raveling detection; 2) computation of each subsection with the newly developed feature set for raveling analysis; 3) raveling classification using random forest models; post-processing to smooth isolated subsections in the six subsection-based raveling classification outcomes for determining the raveling severity level; and aggregation of the detection outcomes to segment-level raveling measurement and report the raveling condition at the segment level based on highway agencies’ survey practices. Without loss of generality, the developed algorithms have been tested and validated using the pavement condition survey protocol in the Georgia Department of Transportation (GDOT). The algorithms can be extended to other highway agencies’ pavement condition survey protocols by re-training the classification components using corresponding ground truth data. The proposed algorithms demonstrated promising capabilities to automatically detect and measure asphalt pavement raveling. Using the proposed algorithms will, potentially, save manual effort in field surveys, improve data accuracy, and help highway agencies make more informed decisions on pavement maintenance and rehabilitation. The developed algorithms are based on 3D pavement data that had been already collected, which eliminates the need to make additional effort for data collections.

This NCHRP-IDEA investigation was conducted by Georgia Institute of Technology.

NCHRP IDEA Project 163

English

50p

2015-12

NCHRP-IDEA Program Project Final Report

Final Report

Digital/other

Figures; Photos; References; Tables

Algorithms; Asphalt pavements; Lasers; Macrotexture; Stripping (Pavements)

Innovations Deserving Exploratory Analysis (IDEA) (Program)

Highways; Pavements

TRIS, TRB, ATRI

Mar 18 2016 2:57PM