Ishikawa Group Laboratory | Accurate and Robust Inter-vehicle Distance Estimation with Stereo High-speed Vision @IshikawaLab | Uploaded 1 year ago | Updated 2 hours ago
We propose an accurate and robust inter-vehicle distance estimation method using high-speed stereo vision. The framework involves two driving mechanisms. The first mechanism performs accurate and stable tracking with an algorithm optimized for stereo high-speed vision even under intensive vibration. The second mechanism estimates inter-vehicle distance via a highly accurate scale estimation and aggregates multiple scale-based distance estimations to ensure that it is more accurate and robust even in situations where the scale changes rapidly (e.g., emergency braking).
We demonstrated the proposed system in three different scenes. In the first scene, we were following a truck on the highway, which is the most common situation in truck platooning. We can see the bounding box of the truck and its distance from the ego vehicle. The estimated relative velocity and acceleration are also displayed in the speedometers below. Although the front truck was slightly tilted when approaching a curve, we can see that the bounding box is pretty stable and the distance is estimated accurately. In the second scene, a parked truck that was more than 100m away was approached at about 10m by sudden acceleration and braking. As we can see, the distance, velocity, and acceleration can be estimated stably without losing track even in a situation where relative velocity and acceleration are quite high. In the last scene, both the front vehicle and the ego-vehicle were suffering intensive vibration and the slope was changing in the middle of the scene. Even in this challenging situation, we can see that the front vehicle can be stably tracked, and accurate distance estimation can be achieved.
Visit our project page for more information.
Project page: ishikawa-vision.org/fusion/InterVehicleDistance/index-e.html
We propose an accurate and robust inter-vehicle distance estimation method using high-speed stereo vision. The framework involves two driving mechanisms. The first mechanism performs accurate and stable tracking with an algorithm optimized for stereo high-speed vision even under intensive vibration. The second mechanism estimates inter-vehicle distance via a highly accurate scale estimation and aggregates multiple scale-based distance estimations to ensure that it is more accurate and robust even in situations where the scale changes rapidly (e.g., emergency braking).
We demonstrated the proposed system in three different scenes. In the first scene, we were following a truck on the highway, which is the most common situation in truck platooning. We can see the bounding box of the truck and its distance from the ego vehicle. The estimated relative velocity and acceleration are also displayed in the speedometers below. Although the front truck was slightly tilted when approaching a curve, we can see that the bounding box is pretty stable and the distance is estimated accurately. In the second scene, a parked truck that was more than 100m away was approached at about 10m by sudden acceleration and braking. As we can see, the distance, velocity, and acceleration can be estimated stably without losing track even in a situation where relative velocity and acceleration are quite high. In the last scene, both the front vehicle and the ego-vehicle were suffering intensive vibration and the slope was changing in the middle of the scene. Even in this challenging situation, we can see that the front vehicle can be stably tracked, and accurate distance estimation can be achieved.
Visit our project page for more information.
Project page: ishikawa-vision.org/fusion/InterVehicleDistance/index-e.html
