NCHRP Implementation Support Program. Implementation of Asphalt Pavement Raveling Detection Algorithm
| 项目名称： | NCHRP Implementation Support Program. Implementation of Asphalt Pavement Raveling Detection Algorithm |
| 摘要： | Raveling (loss of aggregates) is one of the important asphalt pavement distresses. State DOTs like Florida DOT, Georgia DOT, and Alabama DOT use Open-graded Friction Course (OGFC) pavements; raveling is one of the most predominant pavement distresses on OGFC pavements. However, current practices for visual inspection of raveling severity levels are time-consuming, labor-intensive, and subjective. NCHRP IDEA 20-30/IDEA 163 has successfully developed an automatic raveling classification algorithm using 3D pavement data, macro-texture analysis, and ML modeling. Different ML models have been critically evaluated; the most effective ML model has been identified, and an automatic raveling classification algorithm using ML, macro-texture analysis, and 3D pavement surface data has been developed. The developed automatic raveling classification algorithm uses the 3D pavement surface data already collected by state Departments of Transportation (DOTs) for pavement evaluation of cracking and rutting, so no extra data collection effort is necessary. The output from the automatic raveling classification algorithm is the severity level (severe/3, medium/2, and low/1) based on the 3D pavement images collected at different image sizes (e.g., 5-meter or 8-meter intervals) as specified by the different 3D sensing systems used. NCHRP 20-44(50) proposes to pilot the developed automatic raveling classification algorithm for improving the current visual inspection of raveling using 3D pavement data. |
| 状态： | Proposed |
| 资金： | 225000 |
| 资助组织： | National Cooperative Highway Research Program；American Association of State Highway and Transportation Officials (AASHTO)；Federal Highway Administration |
| 项目负责人： | Mohan, Sid |
| 开始时间： | 20221101 |
| 主题领域： | Highways；Maintenance and Preservation；Pavements |
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