3 ms·

LIDAR works _through_ reflections. It essentially paints out the surrounding area with laser pulses and then measures the time for those pulses to come back. Si

LIDAR works _through_ reflections. It essentially paints out the surrounding area with laser pulses and then measures the time for those pulses to come back. Since lasers travel at the speed of light, this time-to-return is quite small and hence they need quite accurate clocks (which is where a lot of the expense comes in). That being said, laser range-finding works well on diffuse surfaces; this is because when diffuse surfaces reflect, they reflect the incoming light in a broad hemisphere (or cone) which sends the laser pulse out in many directions. Consequently, the surface to measure can be at a variety of angles and still be picked up by the LIDAR sensors (the sensor doesn't care about strength, only time-to-return) So in terms of "weirdly reflective" surfaces out there, almost everything is diffuse enough for LIDAR to work well. Car hoods, carbon fiber, chrome wheel covers, etc. The only exception is glass, where generally lasers travel straight through and don't return to the sensors. So LIDAR actually detects "holes" in these situations, as if other cars were driving with no windshield an all their windows down. So the only real risk would be a large plane of glass in the middle of the highway with completely normal road behind it. LIDAR would miss the glass, and the cameras would not be able to see it either. Most real drivers would fail at that too though :D

daenz 14y ago
I guess what I meant was, surely there are weird surfaces that have multiple bounces. Or light being emitted could bounce between 2 cars and back to the sensor...or off a shop window (at a high angle, fresnel reflection), back onto something else, and back into the sensor. This data would come back into the sensor and it wouldn't be expected. So surely the automated car, when it sees data it does not expect, does not stop, because it must see data it does not expect often through multiple bounces, right?
- xxbondsxx 14y ago
  Sure, the situation you described certainly happens and is just considered a general noisy measurement. The car could detect empty road one second and all of the sudden some small object _right_ in front of the grill at the next frame. To avoid this "freakout" situation where the car slams on the brakes every time a noisy measurement comes in, all the data is passed through a particle filter (or Kalman filter) first before being processed by the AI. The transition model of the cars environment is known, so it can reason that "there is a very small chance this reading represents a real object and is not noise, because i did not detect anything near this position over the last 20 frames, so I'm going to assign a very low probability to it." Hence you can clean up the data really well because you're measuring an outdoor environment, not a meteor shower (or anything else where objects could appear and disappear every frame due to high velocity).
yread 14y ago
What about a fence - the wires reflect the light but they make up perhaps 5% of the crossection - the LIDAR could "see" only the holes
- Schwolop 14y ago
  Radar can handle that problem. To be fair, probably not the automative radars they're already using, but something in the tens of GHz range could do it.

daenz 14y ago

I guess what I meant was, surely there are weird surfaces that have multiple bounces. Or light being emitted could bounce between 2 cars and back to the sensor...or off a shop window (at a high angle, fresnel reflection), back onto something else, and back into the sensor. This data would come back into the sensor and it wouldn't be expected. So surely the automated car, when it sees data it does not expect, does not stop, because it must see data it does not expect often through multiple bounces, right?

xxbondsxx 14y ago
Sure, the situation you described certainly happens and is just considered a general noisy measurement. The car could detect empty road one second and all of the sudden some small object _right_ in front of the grill at the next frame. To avoid this "freakout" situation where the car slams on the brakes every time a noisy measurement comes in, all the data is passed through a particle filter (or Kalman filter) first before being processed by the AI. The transition model of the cars environment is known, so it can reason that "there is a very small chance this reading represents a real object and is not noise, because i did not detect anything near this position over the last 20 frames, so I'm going to assign a very low probability to it." Hence you can clean up the data really well because you're measuring an outdoor environment, not a meteor shower (or anything else where objects could appear and disappear every frame due to high velocity).

yread 14y ago

What about a fence - the wires reflect the light but they make up perhaps 5% of the crossection - the LIDAR could "see" only the holes

Schwolop 14y ago
Radar can handle that problem. To be fair, probably not the automative radars they're already using, but something in the tens of GHz range could do it.