Artificial Intelligence for Pavement Condition Assessment from 2D/3D Surface Images
| 项目名称： | Artificial Intelligence for Pavement Condition Assessment from 2D/3D Surface Images |
| 摘要： | While manual quality assurance is inefficient and expensive, the proprietary data storing and processing methods have prevented Texas Department of Transportation (TxDOT) from developing automated methods for data validation. Recently, with the national initialization of standard format for two-dimensional/three-dimensional (2D/3D) pavement surface images and the development of Artificial Intelligence (AI)/Machine Learning (ML) in Computer Vision, TxDOT sees the opportunity of developing new methods for automated pavement condition assessment, with more independence from vendors and their equipment. The main objective of this research is to develop ML-based application software to assess pavement conditions using the standard format 2D/3D pavement surface images. The three main components of this research include the development of a standard format 2D/3D pavement surface image library, a set of ML models for pavement distress measurement, and application software for pavement condition evaluation. The proposed project will assist TxDOT to enhance the quality of the automated pavement condition data, which would eventually help the State of Texas improve its pavement performance. |
| 状态： | Active |
| 资金： | 451875 |
| 资助组织： | Texas Department of Transportation |
| 管理组织： | Texas Department of Transportation |
| 项目负责人： | Adediwura, Jade |
| 执行机构： | Texas State University, San Marcos |
| 主要研究人员： | Wang, Feng |
| 开始时间： | 20220901 |
| 预计完成日期： | 20250831 |
| 主题领域： | Data and Information Technology；Highways；Maintenance and Preservation；Pavements |
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