Radar and LiDAR Fusion for Scaled Vehicle Sensing
| 项目名称： | Radar and LiDAR Fusion for Scaled Vehicle Sensing |
| 摘要： | R&D platforms and robust prototypes are essential for the development and demonstration of automated driving functions. Thousands of hours of safety and performance benchmarks must be met before an ADAS system is production-ready. However, full-scale test-beds are expensive to make, labor-intensive to design, and include inherent safety risks when testing. To reduce these risks and expenses, scaled prototypes can be developed to model system design and vehicle behavior in targeted driving scenarios. Scaled test-beds can improve the ease of safety-testing future ADAS systems and can help visualize test results and system limitations to audiences with varying technical backgrounds better than software simulations. However, though small-scaled vehicles can accommodate similar on-board systems to its full-scale counterparts, the performance of these systems (particularly sensors) can be affected. For example, as the vehicle scales down, the resolution from perception sensors and the performance for object tracking decreases, especially from mounted radars. With many automated driving functions relying on radar tracking, the small-scaled vehicle must overcome the reduced tracking ability at scale in order to provide safe and accurate system modeling. This project proposes a sensor fusion approach to augment radar data in a scaled environment that uses an off-the-shelf LiDAR as a high spatial resolution sensor. It is expected that, with this approach, radar tracking software (RTS) developed at full-scale will also reliably operate in small-scale environments. Successfully implementing radar and LiDAR fusion, system tests with scaled test-bed vehicles can then identify safety concerns in ADAS functions more quickly and efficiently, leading to faster and safer product development. |
| 状态： | Active |
| 资金： | 142049 |
| 资助组织： | Office of the Assistant Secretary for Research and Technology |
| 项目负责人： | Glenn, Eric Zachary |
| 执行机构： | Virginia Tech Transportation Institute |
| 开始时间： | 20191125 |
| 预计完成日期： | 20210630 |
| 主题领域： | Data and Information Technology；Highways；Safety and Human Factors；Vehicles and Equipment |
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