3 ms·

i believe (and someone correct me if wrong) that driving on the interstate (and self driving cars/trucks) is a somewhat [way] easier problem than driving on any

i believe (and someone correct me if wrong) that driving on the interstate (and self driving cars/trucks) is a somewhat [way] easier problem than driving on any road. you’re not going to get a lot of value from what you’re proposing, but it’s going to be super expensive.

IgorPartola 7y ago
In theory, theory and practice are the same. In practice, not so much. Sure, we may see prototypes of self-driving cars going on the interstate in California on sunny days. But I have yet to see a self-driving car make it through a blizzard in Montana. You can't see lane markings with a LIDAR if you can't see the road covered in an inch of hard packed snow. But radio signals of correct frequencies have no problem with that. Think about it this way: the roads themselves are very expensive. But they make each car much cheaper. Most cars don't have to be equipped to drive over rocks and roots (we have tarmac), or lakes/ponds/rivers (we have bridges). We already spend a ton of taxpayer money to make it so that a 15 inch wheel with a mostly smooth tire and 5" of suspension travel is all a car needs. Why not install transceivers to make cars not require to have a super complicated LIDAR system?
- bitL 7y ago
  LiDAR is just one small sensor fusion component in self-driving cars. There are up to 6 LiDARs, up to 4 radars, many cameras and sonic sensors that provide a stream of data for SLAM. The algorithms we have for perception right now are sufficient for 99.9% situations already, although not in real-time with the current technology. Once we surpass 200Hz, we should be fine. On the other hand, path planning is still in the stone age and there is not much hope it'd get better anytime soon (full of NP-Hard problems).
  - IgorPartola 7y ago
    Last I checked, the limiting factor was the fact that they couldn't build a complex enough LIDAR that was both small and cheap.
    - bitL 7y ago
      That has no effect on perception quality, just on economy & production. The problem is "solved" research-wise, it's just about miniaturization, speeding it up etc. in evolutionary way as semiconductors and materials improve. Path planning is on another orbit, not solved even in theory...

IgorPartola 7y ago

In theory, theory and practice are the same. In practice, not so much. Sure, we may see prototypes of self-driving cars going on the interstate in California on sunny days. But I have yet to see a self-driving car make it through a blizzard in Montana. You can't see lane markings with a LIDAR if you can't see the road covered in an inch of hard packed snow. But radio signals of correct frequencies have no problem with that. Think about it this way: the roads themselves are very expensive. But they make each car much cheaper. Most cars don't have to be equipped to drive over rocks and roots (we have tarmac), or lakes/ponds/rivers (we have bridges). We already spend a ton of taxpayer money to make it so that a 15 inch wheel with a mostly smooth tire and 5" of suspension travel is all a car needs. Why not install transceivers to make cars not require to have a super complicated LIDAR system?

bitL 7y ago
LiDAR is just one small sensor fusion component in self-driving cars. There are up to 6 LiDARs, up to 4 radars, many cameras and sonic sensors that provide a stream of data for SLAM. The algorithms we have for perception right now are sufficient for 99.9% situations already, although not in real-time with the current technology. Once we surpass 200Hz, we should be fine. On the other hand, path planning is still in the stone age and there is not much hope it'd get better anytime soon (full of NP-Hard problems).
- IgorPartola 7y ago
  Last I checked, the limiting factor was the fact that they couldn't build a complex enough LIDAR that was both small and cheap.
  - bitL 7y ago
    That has no effect on perception quality, just on economy & production. The problem is "solved" research-wise, it's just about miniaturization, speeding it up etc. in evolutionary way as semiconductors and materials improve. Path planning is on another orbit, not solved even in theory...