5 ms·

Right, so what happens when one says wall, and one says clear air? You brake? That is what happens now with phantom braking. Approaching a bridge? camera sees

Right, so what happens when one says wall, and one says clear air? You brake? That is what happens now with phantom braking. Approaching a bridge? camera sees air, radar sees wall, slam on brakes. You want the best sensor type over a high-fidelity sensor and a lower fidelity sensor. The Tesla system has 8 cameras (3 forward), so they def have overlap between what they are considering better cameras. Time will prove which approach wins.

BugsJustFindMe 5y ago
The post I was responding to said lidar, not radar. But if you want to switch to radar, we can talk about that too. > camera sees air, radar sees wall, slam on brakes Seeing bridges as walls is not a fundamental property of radar. That's an implementation problem. If cars are doing radar poorly, maybe the fix is to start doing it less poorly instead of throwing it away entirely.
- brianwawok 5y ago
  Well, that was specifically about blending two different sensors with different characteristics. For you walking, it would be like blending your eyes with your nose. If your eyes tells you the floor is safe, and your nose smells something bad, do you stop? Anytime you have two different sensors with different characteristics, you want "the best". Your body uses your eyes to see where to walk, and your nose to test if pizza is rotten. Blending multiple sensor types is tricky. So back to LIDAR.. same difference. Camera and LIDAR have different profiles. I think it's fine to use either, but I think trying to blend the two is a sub-optimal solution to the problem. Again, this is my guess from what I know. I could be wrong, and the winning technology could use 12 different sensors (vision + radar + lidar + smell + microphones), and blend them all to drive. Cool if someone pulls it off! But if I had to do it myself or place a bet, I would put it on a single sensor type.
  - BugsJustFindMe 5y ago
    Unfortunately your example is inapt because the center of your vision and your peripheral vision may as well be entirely separate systems that don't overlap, and the way brains apply focus doesn't translate to how cameras work. Your scenario is closer to asking about the center of your focus saying the path in front of you is clear and your peripheral vision detecting inbound motion from the side. Peripheral motion detection overrides the clear forward view, but it's because they aren't trying to record the same information. Here's why: > If your eyes tells you the floor is safe, and your nose smells something bad, do you stop? Absolutely, yes, if the bad smell smells like dog shit or vomit or something else that I definitely don't want to step in. If I'm walking, I'm very unlikely to be looking directly at my feet and much more likely to be looking ahead to do predictive path planning. I definitely do stop at least transiently in your scenario and then apply extra visual focus to the ground right in front of my feet so that I don't step on dog shit. The center of my vision is great at discerning details, but peripheral vision is terrible for that. Anyway, the obvious answer to your inquiry based on my explanation here is to use confidence weighting and adaptive focus. If I think something might be happening somewhere, I focus my available resources directly at the problem.
    - patentatt 5y ago
      This. When sensors disagree, you need to proceed with caution by taking a defensive stance and seek out more information. If a self-driving car can’t do that, then it can’t self drive really. I’m bearish on self driving, my uninformed take is that it is something that will require very near general AI to pull off acceptably. So it’s kind of silly, again in my totally uninformed opinion, to focus on using our current methods to do self driving. The focus needs to be on pushing toward general AI first, then just ask it to drive.
  - baud147258 5y ago
    > If your eyes tells you the floor is safe, and your nose smells something bad well, if I'm smelling gas, I know the situation isn't safe… (and thus my nose is giving me an information my eyes might not have detected)
  - threeseed 5y ago
    > but I think trying to blend the two is a sub-optimal solution to the problem Research over the last decade has shown that LiDAR/Vision fusion outperforms Vision Only. Can you explain the science behind your position ?
  - tw04 5y ago
    > If your eyes tells you the floor is safe, and your nose smells something bad, do you stop? If my eyes tell me the floor is safe, but my ears hear it creaking and my feet feel it sagging I'm going to stop in my tracks/back up. If Tesla can't handle correlating multiple different types of sensors they aren't ever replacing a human driver.
  - a-dub 5y ago
    sensor fusion is used in a lot of places in robotics (and rockets!). and yes, your percept is constructed from all functioning senses. what you look at and where your attention lands is often directed by your auditory system which can locate things in 3d space.
viraptor 5y ago
> Approaching a bridge? camera sees air, radar sees wall, slam on brakes. That's simplifying the situation a bit too much. The camera can give more results than air/not-air. Specifically in this case it could detect a bridge. Same applies to the radar really - you'll get measurements from multiple heights which would tell you that it may be an inclined street, not a wall.
- brianwawok 5y ago
  I think you are missing parts. Have you watched this video from someone actually working in the field? https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s
- CyanLite2 5y ago
  This is where pre-mapped roadways help. Just an internal GPS database sent down to your car that says "Hey, at this GPS coordinate, there's a bridge here. Here's how to navigate over it." Everywhere else the cars can use radar+camera. GM (SuperCruise) and Ford (BlueCruise) do this today.
flowerlad 5y ago
If you have redundant AOA sensors on a plane and they disagree what do you do? Alert the pilot. You have to do the same on a self-driving car as well. You can't just ignore a serious malfunction, or pretend to not see it just because you don't know to handle it! To be truly redundant you have to use different technologies, such as camera and lidar.
- brianwawok 5y ago
  > If you have redundant AOA sensors on a plane and they disagree what do you do? Alert the pilot. Right, which means it's not a solution for L4/L5 autonomy, only for L2. Tesla is trying to reach L4/L5, so just alerting the pilot is not satisfying the design goal. > To be truly redundant you have to use different technologies, such as camera and lidar. I think that is an opinion and not a fact. Watch a video such as https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s from someone working on this problem
  - flowerlad 5y ago
    > Tesla is trying to reach L4/L5, so just alerting the pilot is not satisfying the design goal. Neither is ignoring it. If a product can't meet the design goals under certain circumstances should it ignore it, not even look for it, or alert the user that there is a catastrophic failure? > I think that is an opinion and not a fact. I think it is more common sense than anything else.
  - thatguy0900 5y ago
    How about they reach lvl 4/5 performance and then they can turn off the lidar then. Because right now, the car is steering into plain view obstacles. That's what they need to worry about, not whether stopping the crashes now goes against their lvl 4 philosophy.
- bumby 5y ago
  >To be truly redundant you have to use different technologies, such as camera and lidar. This isn't necessarily true. From a reliability engineering perspective it depends on the modes of failure and the probability of each mode. If the probability of an AOA failure is low enough, you can reach your designed risk level by having two identical and redundant components. It all comes down the level of acceptable risk.
bumby 5y ago
>That is what happens now with phantom braking. Uber seemed to have programmed an artificial delay when the system got confused. There's a good breakdown of the timeline showing how the system kept misclassifying the bicyclist who was killed, but I couldn't immediately find it. That breakdown shows their strategy at implementing delays in the decision process. According to the NTSB report[1]: >"According to Uber, emergency braking maneuvers are not enabled while the vehicle is under computer control, to reduce the potential for erratic vehicle behavior" When I read that in the context of the programmed delays it seems to indicate "we wanted to avoid nuisance braking so we put in a delay when the system was confused." As someone who used to work in safety-critical software, it blows my mind that you would deliberately hobble one of your main risk mitigations because your system gets confused. While TSLA may be focusing on a platform that gets better data with better sensors, they still need to translate it to better decisions. [1] https://www.ntsb.gov/investigations/AccidentReports/Reports/HWY18MH010-prelim.pdf https://www.ntsb.gov/investigations/AccidentReports/Reports/...
- baud147258 5y ago
  > "we wanted to avoid nuisance braking so we put in a delay when the system was confused." As someone who used to work in safety-critical software, it blows my mind that you would deliberately hobble one of your main risk mitigations because your system gets confused Maybe it was put in place to avoid erratic braking in absence of obstacle, in order to avoid getting hit in the rear by other vehicles (whose driver wouldn't see any obstacle and be unprepared for the Tesla car braking).
  - bumby 5y ago
    That's a good point and might have been their rationale, but I would argue it wasn't a very good risk mitigation because while they reduced the risk in one area (being rear ended) they increased their risk elsewhere. Worse yet, it increased the risk in an area more prone to higher severity incidents (e.g., hitting pedestrians - I assume - carries a higher severity than being rear-ended)
    - 5y ago

BugsJustFindMe 5y ago

The post I was responding to said lidar, not radar. But if you want to switch to radar, we can talk about that too. > camera sees air, radar sees wall, slam on brakes Seeing bridges as walls is not a fundamental property of radar. That's an implementation problem. If cars are doing radar poorly, maybe the fix is to start doing it less poorly instead of throwing it away entirely.

brianwawok 5y ago
Well, that was specifically about blending two different sensors with different characteristics. For you walking, it would be like blending your eyes with your nose. If your eyes tells you the floor is safe, and your nose smells something bad, do you stop? Anytime you have two different sensors with different characteristics, you want "the best". Your body uses your eyes to see where to walk, and your nose to test if pizza is rotten. Blending multiple sensor types is tricky. So back to LIDAR.. same difference. Camera and LIDAR have different profiles. I think it's fine to use either, but I think trying to blend the two is a sub-optimal solution to the problem. Again, this is my guess from what I know. I could be wrong, and the winning technology could use 12 different sensors (vision + radar + lidar + smell + microphones), and blend them all to drive. Cool if someone pulls it off! But if I had to do it myself or place a bet, I would put it on a single sensor type.
- BugsJustFindMe 5y ago
  Unfortunately your example is inapt because the center of your vision and your peripheral vision may as well be entirely separate systems that don't overlap, and the way brains apply focus doesn't translate to how cameras work. Your scenario is closer to asking about the center of your focus saying the path in front of you is clear and your peripheral vision detecting inbound motion from the side. Peripheral motion detection overrides the clear forward view, but it's because they aren't trying to record the same information. Here's why: > If your eyes tells you the floor is safe, and your nose smells something bad, do you stop? Absolutely, yes, if the bad smell smells like dog shit or vomit or something else that I definitely don't want to step in. If I'm walking, I'm very unlikely to be looking directly at my feet and much more likely to be looking ahead to do predictive path planning. I definitely do stop at least transiently in your scenario and then apply extra visual focus to the ground right in front of my feet so that I don't step on dog shit. The center of my vision is great at discerning details, but peripheral vision is terrible for that. Anyway, the obvious answer to your inquiry based on my explanation here is to use confidence weighting and adaptive focus. If I think something might be happening somewhere, I focus my available resources directly at the problem.
  - patentatt 5y ago
    This. When sensors disagree, you need to proceed with caution by taking a defensive stance and seek out more information. If a self-driving car can’t do that, then it can’t self drive really. I’m bearish on self driving, my uninformed take is that it is something that will require very near general AI to pull off acceptably. So it’s kind of silly, again in my totally uninformed opinion, to focus on using our current methods to do self driving. The focus needs to be on pushing toward general AI first, then just ask it to drive.
- baud147258 5y ago
  > If your eyes tells you the floor is safe, and your nose smells something bad well, if I'm smelling gas, I know the situation isn't safe… (and thus my nose is giving me an information my eyes might not have detected)
- threeseed 5y ago
  > but I think trying to blend the two is a sub-optimal solution to the problem Research over the last decade has shown that LiDAR/Vision fusion outperforms Vision Only. Can you explain the science behind your position ?
- tw04 5y ago
  > If your eyes tells you the floor is safe, and your nose smells something bad, do you stop? If my eyes tell me the floor is safe, but my ears hear it creaking and my feet feel it sagging I'm going to stop in my tracks/back up. If Tesla can't handle correlating multiple different types of sensors they aren't ever replacing a human driver.
- a-dub 5y ago
  sensor fusion is used in a lot of places in robotics (and rockets!). and yes, your percept is constructed from all functioning senses. what you look at and where your attention lands is often directed by your auditory system which can locate things in 3d space.

viraptor 5y ago

> Approaching a bridge? camera sees air, radar sees wall, slam on brakes. That's simplifying the situation a bit too much. The camera can give more results than air/not-air. Specifically in this case it could detect a bridge. Same applies to the radar really - you'll get measurements from multiple heights which would tell you that it may be an inclined street, not a wall.

brianwawok 5y ago
I think you are missing parts. Have you watched this video from someone actually working in the field? https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s
CyanLite2 5y ago
This is where pre-mapped roadways help. Just an internal GPS database sent down to your car that says "Hey, at this GPS coordinate, there's a bridge here. Here's how to navigate over it." Everywhere else the cars can use radar+camera. GM (SuperCruise) and Ford (BlueCruise) do this today.

flowerlad 5y ago

If you have redundant AOA sensors on a plane and they disagree what do you do? Alert the pilot. You have to do the same on a self-driving car as well. You can't just ignore a serious malfunction, or pretend to not see it just because you don't know to handle it! To be truly redundant you have to use different technologies, such as camera and lidar.

brianwawok 5y ago
> If you have redundant AOA sensors on a plane and they disagree what do you do? Alert the pilot. Right, which means it's not a solution for L4/L5 autonomy, only for L2. Tesla is trying to reach L4/L5, so just alerting the pilot is not satisfying the design goal. > To be truly redundant you have to use different technologies, such as camera and lidar. I think that is an opinion and not a fact. Watch a video such as https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s https://www.youtube.com/watch?v=eOL_rCK59ZI&t=28286s from someone working on this problem
- flowerlad 5y ago
  > Tesla is trying to reach L4/L5, so just alerting the pilot is not satisfying the design goal. Neither is ignoring it. If a product can't meet the design goals under certain circumstances should it ignore it, not even look for it, or alert the user that there is a catastrophic failure? > I think that is an opinion and not a fact. I think it is more common sense than anything else.
- thatguy0900 5y ago
  How about they reach lvl 4/5 performance and then they can turn off the lidar then. Because right now, the car is steering into plain view obstacles. That's what they need to worry about, not whether stopping the crashes now goes against their lvl 4 philosophy.
bumby 5y ago
>To be truly redundant you have to use different technologies, such as camera and lidar. This isn't necessarily true. From a reliability engineering perspective it depends on the modes of failure and the probability of each mode. If the probability of an AOA failure is low enough, you can reach your designed risk level by having two identical and redundant components. It all comes down the level of acceptable risk.

bumby 5y ago

>That is what happens now with phantom braking. Uber seemed to have programmed an artificial delay when the system got confused. There's a good breakdown of the timeline showing how the system kept misclassifying the bicyclist who was killed, but I couldn't immediately find it. That breakdown shows their strategy at implementing delays in the decision process. According to the NTSB report[1]: >"According to Uber, emergency braking maneuvers are not enabled while the vehicle is under computer control, to reduce the potential for erratic vehicle behavior" When I read that in the context of the programmed delays it seems to indicate "we wanted to avoid nuisance braking so we put in a delay when the system was confused." As someone who used to work in safety-critical software, it blows my mind that you would deliberately hobble one of your main risk mitigations because your system gets confused. While TSLA may be focusing on a platform that gets better data with better sensors, they still need to translate it to better decisions. [1] https://www.ntsb.gov/investigations/AccidentReports/Reports/HWY18MH010-prelim.pdf https://www.ntsb.gov/investigations/AccidentReports/Reports/...

baud147258 5y ago
> "we wanted to avoid nuisance braking so we put in a delay when the system was confused." As someone who used to work in safety-critical software, it blows my mind that you would deliberately hobble one of your main risk mitigations because your system gets confused Maybe it was put in place to avoid erratic braking in absence of obstacle, in order to avoid getting hit in the rear by other vehicles (whose driver wouldn't see any obstacle and be unprepared for the Tesla car braking).
- bumby 5y ago
  That's a good point and might have been their rationale, but I would argue it wasn't a very good risk mitigation because while they reduced the risk in one area (being rear ended) they increased their risk elsewhere. Worse yet, it increased the risk in an area more prone to higher severity incidents (e.g., hitting pedestrians - I assume - carries a higher severity than being rear-ended)
  - 5y ago