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Vision is probablistic. You can improve your probabilities with more data and deeper nets, but the probability is never 100%. Inferring depth using triangulatio

Vision is probablistic. You can improve your probabilities with more data and deeper nets, but the probability is never 100%. Inferring depth using triangulation of extracted features using vision is also probabilistic. Lidar gives you very rudimentary depth and positional data, but it is precise, and reliable, and the false positives are low. Lidar is not seeing the world as a series of probabilistic phantasms that may or may not be a pedestrian, or a jersey barrier, or whatever. Elon said: "Lidar is lame! Lidar is Lame! lame lame lame lame." But then he later said: "We've gone over this multiple times. Are we sure we have the right sensor suite? Are we sure we have everything we need?.... No." Lidar is a crutch and we'll see how hard Tesla is limping in a couple years when Elon is claiming They're going to have Robotaxis. To Tesla's credit, it is theoretically possible to develop a fully autonomous vehicle without needing Lidar, but before you can deploy, you need to integrate Lidar, and it can be retrofitted as a largely independent system, necessary for it's enhanced redundancy, but not needed for informing the planner, except when the Lidar is seeing things the vision system isn't. The presentation was a pretty good run down on various techniques and methods that are being utilized by different autonomy developers. The downside is that everything is framed as a rationalization as to why Tesla has some kind of secret weapon, when they're mostly doing conventional things, and not all the conventional things you need to build a complete autonomous vehicle. I was waiting for Elon or Karpathy to trot out the magic pixie dust that will have Tesla's driving empty in a couple years, but that was nowhere to be found.

maccam94 8y ago
I believe he claimed that they did have all of the sensors they need with hardware v2, and they had no need for LIDAR. We'll see if that's true. One thing that stood out to me is that he said they only need radar in front because you're only moving fast in that direction. Does that mean the cars will be susceptible to T-bone accidents?
- Fricken 8y ago
  I don't know, I guess it will be born out in the data, but I hope they aren't seriously planning to drive people through busy intersections where T-bones are likely to happen under the auspices that what they've got is a level 3/4 system. Waymo's safetly critical disengagements are at 1 every 11,000 miles. Fender benders happen about once every 100,000 miles, so just on that Waymo is off by an order of magnitude, and Waymo spares no expense on compute or sensors.
  - grey-area 8y ago
    Over how many miles?
- Klathmon 8y ago
  >Does that mean the cars will be susceptible to T-bone accidents? Is there much of anything a car can do to prevent being T-Boned? And even if there is, I don't really see it being something that radar would help much with. If you and another car are approaching perpendicularly, you'll have an almost perfect situation to get positioning and speed information over a pretty short amount of time. Of course I've never done anything even resembling any kind of work in this space, and I don't want to pretend to know the answer, but the claims of side radar not being necessary seems to pass a smoke test.
  - Animats 8y ago
    Is there much of anything a car can do to prevent being T-Boned? Yes. Stop suddenly while entering the intersection when conflicting traffic is detected. Google cars do that, and they have been rear-ended several times because of it. You can find those events in the CA DMV accident reports. Better than being hit by the cross traffic.
- Robotbeat 8y ago
  There are vision systems on the side. The car primarily relies on its vision system, like humans. The radar is a check, not the primary.
metafunctor 8y ago
I think the point was that lidar is too low resolution. You must have very high resolution (in both time and space) to achieve L4 or L5; to accurately determine if a pedestrian is not paying attention, or if a bicyclist is looking to cross the road. Not that Tesla is doing any of that right now, they most likely are not. But a lidar is not going to, either. Not ever, which is the point. I thought the fleet learning aspects Karpathy outlines came pretty damn close to the pixie dust.
- Symmetry 8y ago
  You can achieve L4 before you can determine if a pedestrian is paying attention. Your car will be slowing down when it doesn't have to but it can work and work safely.
  - Fricken 8y ago
    Well, it has to work well enough to be useful. When Waymo reports one disengagement every 11,000 miles, that's just the safety critical disengagements. The total disengagement rate is much higher than that. They are also relying on teleoperators who can help guide the vehicles out of tricky situations, which are myriad and it will take forever for Waymo to build features down to a granular enough level that they can operate reliably enough to compete with Uber.
  - rayiner 8y ago
    Slowing down isn’t always an option and it’s not always safe. (What happens when all the human driven cars keep driving at normal speed? You’ve now created an unsafe traffic condition for everyone.)
- Fricken 8y ago
  Musk would have you think it's a Lidar vs. cameras debate. It's not. It's a Lidar + cameras vs. just cameras debate. Lidar has significant shortcomings. So do cameras. But together they make for a decent perception system. With regards to fleet learning, Tesla has been going on about it for years, but more data is not better. Better data is better. Clifornia's disengagement reports have seen criticism because they place an emphasis on the number of overall miles driven as a useful measure of progress, when actually it doesn't mean much. Companies like Zoox, after spending years doing small-scale closed course testing hit the ground running, and with only 10 vehicles and a few months of driving around San Fransisco they were able to take reporters for autonomous rides, and they took a couple dozen journalists to various pre-designated spots around SF with only one disengagement the whole day. The nice thing about the whole fleet learning narrative is that is makes Tesla drivers feel like they're helping just by driving around.
leesec 8y ago
>"We've gone over this multiple times. Are we sure we have the right sensor suite? Are we sure we have everything we need?.... No." Where did he say this? He repeatedly said they have everything they need to drive. >but before you can deploy, you need to integrate Lidar, Why? >not all the conventional things you need to build a complete autonomous vehicle. No one knows how to make a completely autonomous vehicle because they don't exist. I'll take the billionaire tech genius' approach, whose gotten farther than anyone in this field, over your armchair opinion, thanks.
- tjoff 8y ago
  > whose gotten farther than anyone in this field What they've done so far is a dangerous lane-assistance. From what's seen they are nowhere near waymo. Would hate for tesla and uber to ruin this for everyone else.
- Fricken 8y ago
  There's a reason why nobody else in the industry thinks they can make robotaxis work without Lidar. Of course, if you were familiar with the rest of the industry you wouldn't say Tesla has gotten farther than anybody else in the field, that's just ignorant.
  - leesec 8y ago
    Well I'm a software engineer at an automotive tech company who interfaces with all the big OEM's daily so I'm gonna go ahead and say I'm very familiar. But that's not a reason you know, that's just you diverting.
salty_biscuits 8y ago
"Lidar is not seeing the world as a series of probabilistic phantasms that may or may not be a pedestrian, or a jersey barrier, or whatever" Lidar is inherently probabilistic too,like every sensor is. Just because the photomultiplier voltage rises and some peak detection hardware can correlate it with a transmit pulse, it does not mean that there is a "point" at that position in 3d space. It has different error characteristics to vision sure, but it is still an inference problem with corresponding artifacts to deal with. In fact I would say that the different error characteristics actually make them ideal for sensor fusion, i.e. Lidar for initial depth and vision for filling in the details.
- cromwellian 8y ago
  None of the cars using LIDAR are using LIDAR only, they are fusing LIDAR, radar, maps, and computer vision.

maccam94 8y ago

I believe he claimed that they did have all of the sensors they need with hardware v2, and they had no need for LIDAR. We'll see if that's true. One thing that stood out to me is that he said they only need radar in front because you're only moving fast in that direction. Does that mean the cars will be susceptible to T-bone accidents?

Fricken 8y ago
I don't know, I guess it will be born out in the data, but I hope they aren't seriously planning to drive people through busy intersections where T-bones are likely to happen under the auspices that what they've got is a level 3/4 system. Waymo's safetly critical disengagements are at 1 every 11,000 miles. Fender benders happen about once every 100,000 miles, so just on that Waymo is off by an order of magnitude, and Waymo spares no expense on compute or sensors.
- grey-area 8y ago
  Over how many miles?
Klathmon 8y ago
>Does that mean the cars will be susceptible to T-bone accidents? Is there much of anything a car can do to prevent being T-Boned? And even if there is, I don't really see it being something that radar would help much with. If you and another car are approaching perpendicularly, you'll have an almost perfect situation to get positioning and speed information over a pretty short amount of time. Of course I've never done anything even resembling any kind of work in this space, and I don't want to pretend to know the answer, but the claims of side radar not being necessary seems to pass a smoke test.
- Animats 8y ago
  Is there much of anything a car can do to prevent being T-Boned? Yes. Stop suddenly while entering the intersection when conflicting traffic is detected. Google cars do that, and they have been rear-ended several times because of it. You can find those events in the CA DMV accident reports. Better than being hit by the cross traffic.
Robotbeat 8y ago
There are vision systems on the side. The car primarily relies on its vision system, like humans. The radar is a check, not the primary.

metafunctor 8y ago

I think the point was that lidar is too low resolution. You must have very high resolution (in both time and space) to achieve L4 or L5; to accurately determine if a pedestrian is not paying attention, or if a bicyclist is looking to cross the road. Not that Tesla is doing any of that right now, they most likely are not. But a lidar is not going to, either. Not ever, which is the point. I thought the fleet learning aspects Karpathy outlines came pretty damn close to the pixie dust.

Symmetry 8y ago
You can achieve L4 before you can determine if a pedestrian is paying attention. Your car will be slowing down when it doesn't have to but it can work and work safely.
- Fricken 8y ago
  Well, it has to work well enough to be useful. When Waymo reports one disengagement every 11,000 miles, that's just the safety critical disengagements. The total disengagement rate is much higher than that. They are also relying on teleoperators who can help guide the vehicles out of tricky situations, which are myriad and it will take forever for Waymo to build features down to a granular enough level that they can operate reliably enough to compete with Uber.
- rayiner 8y ago
  Slowing down isn’t always an option and it’s not always safe. (What happens when all the human driven cars keep driving at normal speed? You’ve now created an unsafe traffic condition for everyone.)
Fricken 8y ago
Musk would have you think it's a Lidar vs. cameras debate. It's not. It's a Lidar + cameras vs. just cameras debate. Lidar has significant shortcomings. So do cameras. But together they make for a decent perception system. With regards to fleet learning, Tesla has been going on about it for years, but more data is not better. Better data is better. Clifornia's disengagement reports have seen criticism because they place an emphasis on the number of overall miles driven as a useful measure of progress, when actually it doesn't mean much. Companies like Zoox, after spending years doing small-scale closed course testing hit the ground running, and with only 10 vehicles and a few months of driving around San Fransisco they were able to take reporters for autonomous rides, and they took a couple dozen journalists to various pre-designated spots around SF with only one disengagement the whole day. The nice thing about the whole fleet learning narrative is that is makes Tesla drivers feel like they're helping just by driving around.

leesec 8y ago

>"We've gone over this multiple times. Are we sure we have the right sensor suite? Are we sure we have everything we need?.... No." Where did he say this? He repeatedly said they have everything they need to drive. >but before you can deploy, you need to integrate Lidar, Why? >not all the conventional things you need to build a complete autonomous vehicle. No one knows how to make a completely autonomous vehicle because they don't exist. I'll take the billionaire tech genius' approach, whose gotten farther than anyone in this field, over your armchair opinion, thanks.

tjoff 8y ago
> whose gotten farther than anyone in this field What they've done so far is a dangerous lane-assistance. From what's seen they are nowhere near waymo. Would hate for tesla and uber to ruin this for everyone else.
Fricken 8y ago
There's a reason why nobody else in the industry thinks they can make robotaxis work without Lidar. Of course, if you were familiar with the rest of the industry you wouldn't say Tesla has gotten farther than anybody else in the field, that's just ignorant.
- leesec 8y ago
  Well I'm a software engineer at an automotive tech company who interfaces with all the big OEM's daily so I'm gonna go ahead and say I'm very familiar. But that's not a reason you know, that's just you diverting.

salty_biscuits 8y ago

"Lidar is not seeing the world as a series of probabilistic phantasms that may or may not be a pedestrian, or a jersey barrier, or whatever" Lidar is inherently probabilistic too,like every sensor is. Just because the photomultiplier voltage rises and some peak detection hardware can correlate it with a transmit pulse, it does not mean that there is a "point" at that position in 3d space. It has different error characteristics to vision sure, but it is still an inference problem with corresponding artifacts to deal with. In fact I would say that the different error characteristics actually make them ideal for sensor fusion, i.e. Lidar for initial depth and vision for filling in the details.

cromwellian 8y ago
None of the cars using LIDAR are using LIDAR only, they are fusing LIDAR, radar, maps, and computer vision.