Sidewalk Condition Assessment Leveraging Machine Learning/AI and Mobile LiDAR
| 项目名称： | Sidewalk Condition Assessment Leveraging Machine Learning/AI and Mobile LiDAR |
| 摘要： | This research project seeks to demonstrate the feasibility of mobile LiDAR data as a cost-effective means to support efficient inventory and condition assessment of sidewalks at DDOT. The objective of this research project is twofold: 1) to develop and validate an improved point cloud data processing method that can automatically map pedestrian infrastructures (e.g., sidewalk, curb ramp, etc.) using point cloud data, which will demonstrate its feasibility for network-level analysis (e.g., using Ward 7 as the pilot testing field; 2) if it proves feasible, to apply the developed, automated method to the city-wide mobile LiDAR dataset collected by CycloMedia and generate a complete pedestrian infrastructure map in the entire District. If successful, the outcome of the proposed method in this research project will layout a solid framework toward a sidewalk assessment management program that routinely and cost-effectively inspects, evaluates, and maintains pedestrian infrastructure in the entire District. |
| 状态： | Programmed |
| 资金： | 200000 |
| 资助组织： | District Department of Transportation |
| 管理组织： | Howard University |
| 执行机构： | University of Massachusetts, Amherst |
| 主要研究人员： | Ai, Chengbo |
| 开始时间： | 20220701 |
| 预计完成日期： | 20231231 |
| 主题领域： | Administration and Management；Maintenance and Preservation |
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