Driving Behavioral Learning Leveraging Sensing Information from Innovation Hub
| 项目名称： | Driving Behavioral Learning Leveraging Sensing Information from Innovation Hub |
| 摘要： | The primary goal of this proposal is to develop machine-learning algorithms for driving behavior mining, using real-time vehicle, pedestrian, and infrastructure data. The proposed algorithms will improve our understanding of how people drive on both highways and urban roads, which will help monitor and maintain roadside infrastructure and support the transportation systems to accommodate not only the existing human-driven vehicle but also the upcoming connected and automated mobility systems. The intended outcome of the project is an algorithm suite to learn human behavior patterns from LiDAR and camera datasets. To facilitate its adoption by public agencies, the software will be open-sourced with friendly interface design. The proposed smart mobility testbed concept could be deployed at local intersections and arterial corridors in the City of New Brunswick, NJ and utilized by the Robert Wood Johnson hospital’s patient shuttle services and parking services. |
| 状态： | Active |
| 资金： | 140157 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Caviness, Solomon；Szary, Patrick J |
| 执行机构： | Columbia University<==>Center for Advanced Infrastructure and Transportation |
| 开始时间： | 20210101 |
| 预计完成日期： | 20211231 |
| 主题领域： | Data and Information Technology；Highways；Safety and Human Factors；Vehicles and Equipment |
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