Name
Abstract | ||
|---|---|---|
Tracking road users with high resolution is important for connected vehicles. Due to the complicated environments, tracking objects with a single sensor could not meet the requirements of high-resolution trajectories due to occlusions. How to acquire accurate and complete trajectories based on multisource data is a major challenge for researchers and engineers. This article developed a novel tracking method based on the fusion of roadside light detection and ranging (LiDAR) and camera. According to the relationship between the number of points and distance, the adaptive weight coefficient related to 3-D trajectory information was determined. The performance of the proposed method was evaluated at five selected sites. The proposed tracking method had high performance in terms of speed calculation, tracking range, the rate of object loss, and the repairing rate of disconnected trajectories. The proposed method can benefit many transportation areas, such as traffic volume counting, vehicle speed tracking, and traffic safety analysis. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/TIM.2022.3201938 | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT |
Keywords | DocType | Volume |
Object detection, Trajectory, Three-dimensional displays, Cameras, Point cloud compression, Laser radar, Roads, Adaptive weight, attention mechanism, object detection, object tracking, roadside light detection and ranging (LiDAR) and camera | Journal | 71 |
ISSN | Citations | PageRank |
0018-9456 | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shujian Wang | 1 | 0 | 0.34 |
| Rendong Pi | 2 | 1 | 0.69 |
| Li Jian | 3 | 85 | 31.63 |
| Xinming Guo | 4 | 0 | 0.34 |
| Youfu Lu | 5 | 0 | 0.34 |
| Tao Li | 6 | 0 | 2.03 |
| Yuan Tian | 7 | 0 | 0.34 |