Apparently their radar can only see objects that move.
So, to see this barrier, you'd have to guess its distance from 2D images. That's a hard problem. I think this would be called "obstacle detection using stereo vision" or maybe even "monocular vision" if they're using one camera.
There isn't as much research into this field as there is in systems that use lidar because lidar has been proven to work, and academics probably don't care as much about building their products at massive scales, so the cost of lidar doesn't matter as much.
Searching Arxiv for that phrase [1], the top result is a paper called A Joint 3D-2D based Method for Free Space Detection on Roads [2] that uses Lidar. The next result that doesn't mention lidar is Free Space Estimation using Occupancy Grids and Dynamic Object Detection [3].
Following that is Failing to Learn: Autonomously Identifying Perception Failures for Self-driving Cars [4]. In that paper's conclusion, it states its next plan is to use lidar to improve data quality,
> we plan to incorporate free space computation from the path of the vehicle and from active sensor returns like LIDAR to identify false positives to further improve our assessment and understanding of modern object detectors at the fleet level.
So, to see this barrier, you'd have to guess its distance from 2D images. That's a hard problem. I think this would be called "obstacle detection using stereo vision" or maybe even "monocular vision" if they're using one camera.
There isn't as much research into this field as there is in systems that use lidar because lidar has been proven to work, and academics probably don't care as much about building their products at massive scales, so the cost of lidar doesn't matter as much.
Searching Arxiv for that phrase [1], the top result is a paper called A Joint 3D-2D based Method for Free Space Detection on Roads [2] that uses Lidar. The next result that doesn't mention lidar is Free Space Estimation using Occupancy Grids and Dynamic Object Detection [3].
Following that is Failing to Learn: Autonomously Identifying Perception Failures for Self-driving Cars [4]. In that paper's conclusion, it states its next plan is to use lidar to improve data quality,
> we plan to incorporate free space computation from the path of the vehicle and from active sensor returns like LIDAR to identify false positives to further improve our assessment and understanding of modern object detectors at the fleet level.
[1] https://arxiv.org/find/all/1/all:+AND+vision+AND+stereo+AND+...
[2] https://arxiv.org/pdf/1711.02144.pdf
[3] https://arxiv.org/pdf/1708.04989.pdf
[4] https://arxiv.org/pdf/1707.00051.pdf