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Based on this image: https://images.ctfassets.net/95kuvdv8zn1v/6h1C7lPC79OLOlddEEexqj/1415e6b28c8e4252856f9f341fedc327/GetCruise-Hero-Services.jpg?w=1000&q=80&

• gitfan86 5y ago
  What is success? Does 50 miles of geofenced and daily mapped streets mean Cruise won self driving? What if Waymo gets to 20k miles of geofenced roads and monthly mapped? What if Tesla gets to the point of one intervention/crash every 100k miles? 10M Miles?
  • gonehome 5y ago
    Yeah, they’re not trying to solve the same thing? I think Tesla is right that to solve it for real you need to solve the general case which can’t rely on high resolution maps. The city cab case is smaller and can, so the cruise approach makes sense for that use case. It’s just narrower.
    • ghaff 5y ago
      Or you solve for a subset of highways in a subset of weather conditions. That would be more useful to a lot of people than city cabs which exist today (with human drivers).
    • jowday 5y ago
      The truth of it is that it’s just not possible (with currently existing technology/ML architectures) to create a truly autonomous taxi without HD maps. Everyone in the robotaxi industry knows this - even Tesla builds HD maps, they just don’t call them that.
      • gonehome 5y ago
        My knowledge only comes from Karpathy's talks about this (which are great, worth watching if you haven't seen them). I found his and Tesla's arguments convincing for the general case. That doesn't mean that the narrow cases aren't super cool or valuable (I signed up for this Cruise thing in SF). I just think that if the software is unable to make decisions based on visual data alone without up to date high resolution maps it'll never achieve true FSD in the general case (not geo locked). You'll end up trapped in a local max otherwise because there are just too many conditions in the real world that vary (and the world is too large to economically map fast enough for that approach). You have to solve the vision problem. I don't know enough to comment on the approach differences beyond that, but my understanding was that Tesla did not rely on the same stuff that Waymo and Cruise require (largely Lidar and these high resolution maps).
        • jowday 5y ago
          > I just think that if the software is unable to make decisions based on visual data alone without up to date high resolution maps it'll never achieve true FSD in the general case (not geo locked). You'll end up trapped in a local max otherwise because there are just too many conditions in the real world that vary. My contention is that there’s no way to actually solve for the general case with currently existing technology. The amount of novelty in the real world is too great for any system to account for it without disambiguating via HD maps or remote support. >You have to solve the vision problem. This isn’t a vision problem specifically - even if you had LIDAR and high resolution imaging radar and 8 A100s on every Tesla, “true generalized self driving” wouldn’t be achievable without HD maps with our current understanding of Machine Learning. >My understanding was that Tesla did not rely on the same stuff that Waymo and Cruise require. Tesla maps individual traffic light elements, stop signs, and lane markings, but will attempt to drive even if the area isn’t mapped. Disparities in FSD performance in different areas is largely attributable to some areas being better mapped than others - the mapping data has a huge effect on its performance. There are key elements of the driving task (including recognizing and reacting to every single type of sign other than a stop sign) that FSD can’t do and relies entirely on maps for.
    • justapassenger 5y ago
      > I think Tesla is right that to solve it for real you need to solve the general case which can’t rely on high resolution maps. But they do relay on maps. You cannot use FSD without latest, high resolution maps.
  • danielrhodes 5y ago
    Cruise is interesting insofar as they are not simply looking to sell their technology, but they also want to monetize it as a service. Not only will they not need a driver, they will also be able to buy the hardware (the car) at cost. If it's successful, their margins will be much higher than Uber and Lyft by a long shot.
    • whimsicalism 5y ago
      Is this not what effectively everyone who is doing this (outside of Tesla) is looking at?
    • vkou 5y ago
      As a taxpayer who pays for roads, and suffers from traffic congestion caused by one-occupant and zero-occupant vehicles, I'm eagerly looking forward to reducing the taxes I pay, by taxing those margins, instead. Ideally, the taxes could be high enough that driverless taxis will operate at barely above break-even. The financial comfort of me and my neighbours are more important to me than the profit margins of a firm that barely employs anyone in my town. Unlike a factory or a corporate office (that can threaten to move offshore, eliminating jobs and impoverishing a town), the firm in question is a hostage of local politics - not the other way around.
      • jurassic 5y ago
        Do you think your experience of congestion would be improved by everyone driving private vehicles instead? Not sure I follow the logic here.
        • ghaff 5y ago
          Of course. If one assumes relatively inexpensive rob-taxis people living outside cities will definitely come in more often. I certainly would.
        • vkou 5y ago
          Yes, because in the common case, a taxi (driverless or otherwise) drives empty at least some of the time, to pick someone up, thus creating congestion, compared to a private vehicle, which doesn't drive empty. The cheaper and more convenient you make zero-person and single-person automobile transportation, the more people will use it, and the more congestion they will create. The more expensive and less convenient you make it, the more trips will use non-automotive, or public transportation, both of which produce far less congestion.
  • comex 5y ago
    The human accident rate is about one per 500K miles, so if they were able to get in that range, then yes, they would have succeeded; drivers would be able to stop paying attention to the road without putting themselves and others in danger. But the current FSD beta's intervention rate is more like one per 10 miles, judging from some quick googling. I see no particular reason to assume that incremental improvement can take us from 10 to 500K.
    • waffle_maniac 5y ago
      > current FSD beta's intervention rate is more like one per 10 miles Maybe in rural areas? The videos on YouTube are far more than one per 10 miles. https://www.youtube.com/watch?v=wTybjJj0ptw https://www.youtube.com/watch?v=wTybjJj0ptw
      • whimsicalism 5y ago
        A helpful link for your perusal: https://en.wikipedia.org/wiki/Selection_bias https://en.wikipedia.org/wiki/Selection_bias
        • gitfan86 5y ago
          But are you using confirmation bias to find a cognitive bias that fits here. But, In all seriousness we don't have access to the data across all 60k FSD users to know what the intervention rate is and how it has been changing over time.
          • blahblarblar 5y ago
            Dirty Tesla used to track these stats in his testing and gave up because “it’s not changing”
            • Retric 5y ago
              Which could be a sign some drivers are simply overly cautious. Suppose 1/10 of disconnects prevented a crash, reducing the risk of crashing to 0 only reduces the number of disconnects by 10%. To actually reduce that number you would need to make drivers feel more confident in the vehicle which is a useful metric, but only indirectly relating to safety.
  • stevofolife 5y ago
    Success? Go from point A to point B with minimal incidents. It's not that complicated as most people make out of it.
    • ehsankia 5y ago
      More importantly, "driverless" means no one at the driver seat. What Tesla has is barely even Level 3. Waymo right now is doing rides without anyone in the driverseat, aka Level 4. What Tesla is doing is not driverless.
  • deleted 5y ago
    [deleted]
  • nicbou 5y ago
    I just drove through the Alps, at night, during a snow storm. This is hardly everyday driving, but it's the sort of experience Canadians are no strangers to. Success is when I trust the autopilot to handle the weather conditions where I live, not just sunny days in California.
• ChrisClark 5y ago
  Yeah, but that's not a tech issue. The few thousand that have the full self driving beta just have the opt-in option to turn on rolling stops. That just has to be removed in their next update.
  • borski 5y ago
    As you’ll note in the comments on that thread though, FSD has a lot more issues than just that; particularly with stationary objects and at night.
    • ddlutz 5y ago
      I don't have FSD enabled on my Model 3, but I have the FSD visualization preview. I'd be terrified of FSD at night. During the day I don't see it have any issues registering cars and other obstacles, but during night it barely detects anything.
      • postmeta 5y ago
        Seems fairly good at night in 10.9 https://www.youtube.com/watch?v=01QowBvtraE https://www.youtube.com/watch?v=01QowBvtraE
• sanjoy_das 5y ago
  > It is interesting to me that right now this is sitting on the HN homepage directly adjacent to: "Tesla to recall vehicles that may disobey stop signs (reuters.com)" Based on https://www.forbes.com/sites/bradtempleton/2022/01/13/a-robocar-specialist-gives-tesla-full-self-drive-an-f https://www.forbes.com/sites/bradtempleton/2022/01/13/a-robo... Tesla's FSD has other issues as well.
• pmorici 5y ago
  They are wholly owned by GM are they not? Starting this way doesn’t preclude them taking Tesla’s vision only approach in the future. Even Tesla initially had a radar vision combination approach before moving to pure vision. The real question with whatever technique being used is can they drive the hardware cost low enough that it can be widely deployed.
  • jowday 5y ago
    They moved to pure vision because they were constrained by radar suppliers because of supply chain issues and the chip shortage, not because of any ML progress - they were actually investigating using a higher resolution imaging radar before the pandemic.
    • judge2020 5y ago
      They also have Lidar cars in Fremont that drive around every so often, that doesn't mean they plan to go into every car anytime soon. It'd be short-sighted to not continuously evaluate solutions that previously had constraints (despite what Elon says, they'd add Lidar if it made economic sense and it showed an improvement over camera-only, as their camera detection is pretty accurate these days in FSD).
      • jowday 5y ago
        I’ve seen their LIDAR cars in SF too - if I had to guess they’re gathering ground truth data to train monocular depth models on. And even really naive integrations of LIDAR will show big improvements over camera only. You can do something as simple as overlay the returns from the most recent LIDAR spin over a camera image as a fourth channel and feed it into your models and most of your depth prediction/spatial predictions will improve dramatically.
  • more_corn 5y ago
    The reason camera only won’t happen is because it won’t work. Elon has been fighting reality for years.
• sremani 5y ago
  The question is do the economics of self-driving cars work when you have to add and integrate all these additional equipment. Correct me, if I am wrong but aren't LIDAR cars supposed to cost you $200K+ ? Tesla is imitating humans in a way that removing LIDAR and relying on the compute to make up for them and build more accurate picture. Also, isn't Cruise owned by GM - who are the VCs here?
  • jowday 5y ago
    What makes you say Tesla is imitating humans? Their motion planning is all traditional robotics logic, not anything learned.
    • robotresearcher 5y ago
      Vision-based driving. Humans don't have lidar sensors.
      • jowday 5y ago
        Humans don’t regress per-pixel depth or use convolutions and region proposals to draw bounding boxes around objects. They don’t function on models with fixed weights trained by backprop either. The idea that “vision only” somehow more closely resembles how humans drive quickly falls apart if you inspect the internals of these systems.
        • upbeat_general 5y ago
          I think the comparison comes from the fact that humans infer a 3D map from stereo vision whereas LiDAR to some extent gives you the ground truth 3D map. You’re right that it falls apart pretty quickly though.
          • jowday 5y ago
            Except Tesla isn’t inferring a 3D map from stereo vision either, at least not outside of the front facing cameras - they’re using monocular depth prediction.
• enjoylife 5y ago
  They are betting that hardware combination is the fastest to market, given the constraints of today software. When the ml stack is capable of leveraging purely camera sensors, Cruise and others like them, own the fleet and can swap out the hardware. Tesla does not "own" the fleet per se. So perhaps its different bets on which cars will still be on the road when the ML threshold is crossed.
  • afterburner 5y ago
    Also you can't sell sexy Teslas if they have ugly lidars on top.
    • mikejb 5y ago
      I think it's not just that. When Tesla started to with their FSD journey, they had to determine what sensors they can add to the car. Lidars back then were way more expensive than they are now, and it wouldn't have been feasible to add them at that time. They can't add them now to new vehicles because they promised the vehicles back then are only a software update away from full autonomy [1]. Building on Lidar now would mean developing on 2 heavily differentiating stacks. Going back on the promise of old Tesla's being "FSD capable" would introduce a huge liability. Long story short, Tesla's stance on Lidar determined 8 years ago, without the option to revise the decision with future developments. [1] Note this has turned into "we'll only have to replace the computer in the car", which is still doable, contrary to adding sensors to the existing vehicle.
  • waffle_maniac 5y ago
    Tesla has really fallen behind. I think Karpathy will be fired this year if his team can't achieve at least L4.
    • yupper32 5y ago
      > I think Karpathy will be fired this year if his team can't achieve at least L4. Ah so Karpathy will be fired this year. Because they're not reaching L4. FSD isn't even L3 yet.
• jeffbee 5y ago
  Why do we have to discuss Tesla whenever self-driving comes up? Cruise has this technology. Waymo has it. There are a smattering of niche players out there with various levels of self-driving. Tesla emphatically does not have it. They are not in the race.
  • walrus01 5y ago
    I agree, but they sure claim to be. Literally marketed as "full self driving".
    • B1FF_PSUVM 5y ago
      Actually, I just noticed earlier that todays' wording is ""full self driving capability". Sells for 12k USD here, for instance: https://www.tesla.com/modely/design#overview https://www.tesla.com/modely/design#overview
    • amelius 5y ago
      Musk is a true car salesman.
  • ultrablack 5y ago
    Where can I buy one?
• parkingrift 5y ago
  Tesla will release L4 or L5 self driving this year. Musk said it himself. Please ignore the fact that this is the 7th (or more?) year in a row he has said this.
  • adrr 5y ago
    I still want a functional autopilot that doesn't phantom brake on the freeway which has gotten worse since they stopped relying on radar. Or have the self park feature not curb the wheels. I won't even get started on the summon feature.
    • rurp 5y ago
      The few times I've ridden in a Tesla using "self driving" the phantom breaking was really jarring. It was surprising and concerning how often it slammed on the breaks for no reason.
    • FireBeyond 5y ago
      "Use Summon to bring your vehicle to you while dealing with a fussy child", unless you ask Legal, in which "pay attention to vehicle at all times. Do not use distracted" is the use case, you mean?
• kvogt 5y ago
  Cruise CEO here. Our strategy has been to solve the challenges needed to operate driverless robotaxis on a well-equipped vehicle, then aggressively drive the cost down. Many OEMs are doing this in reverse order. They're trying to squeeze orders of magnitude of performance gains out of really low-cost hardware. Today it's unclear what strategy will win. In a few years our next generation of low-cost compute and sensing lands in these vehicles and our service area will be large enough that you forget there is even a geofence. If OEMs have still not managed to get the necessary performance gains to go fully driverless, we'll know what move was the right one. We shared several details on how our system works and our future plans here: https://www.youtube.com/playlist?list=PLkK2JX1iHuzz7W8z3roCZEqML0G2R9jX8 https://www.youtube.com/playlist?list=PLkK2JX1iHuzz7W8z3roCZ...
  • konschubert 5y ago
    As a bike rider, father, and sometimes inattentive human, I would like to say thank you for the safety you are bringing to our cities.
  • petilon 5y ago
    Congrats on your incredible accomplishment! Thanks for doing this the responsible way. Tesla's approach does not inspire confidence. Starting at the high end, with expensive, reliable tech and slowly bringing the costs (and bulkiness of the equipment) down is the right approach!
    • mensetmanusman 5y ago
      In my experience, expensive doesn’t necessarily mean more reliable, it could just mean higher fidelity, higher resolution (and possibly less reliable due to the utilization of parts ‘less’ produced on the global supply chain), etc. This improved resolution don’t necessarily help an AI grok the situation in real time with >20 Hz response time though.
      • Closi 5y ago
        I think the overall sentiment is more the "let's avoid premature optimisation" rather than "let's spend the most money". If you have pre-sold a 'self driving' capability which you have guaranteed to be backwards compatible on cars you have already sold, then you are effectively cutting out Lidar as an option unless you are going to go back to all those cars and screw it on. And considering that self-driving isn't solved yet, it seems like a bold move to define both your processing power and your sensing hardware in a way which makes it very difficult to (commercially) change.
• oh_sigh 5y ago
  I always wondered why the rejection of lidar by Tesla. My guess is that it is more about profitability/availability than anything else. Just because humans use eyeballs doesn't mean that it is the best bet for a computer. This sort of naturalistic fallacy led people to believe (~130 years ago and beyond) that the ideal flying machines would have flapping wings because, well, birds have wings and that is how they fly. Maybe I'm just salty my 2021 Model Y had lidar stripped out of it, and to me the more tech toys the better. Not that it matters because Tesla FSD is a scam and I wouldn't use it even if it came for free with the car.
  • ra7 5y ago
    Lidar was expensive back then and would've added huge costs to the vehicles. Not to mention, it looked ugly on consumer cars. Elon conveniently used "humans use only vision" as an excuse and promised every Tesla has "sufficient" hardware for full autonomy. It's that premature promise that doesn't let them add sensors even now (and perhaps Elon's ego) without breaking trust and/or eating big costs for retrofitting. In short, Elon made a high risk bet that vision-only would be enough and so far has been proven horribly wrong. But I've got to say, it was brilliantly executed because it gave Tesla mindshare as a tech company, drove sales and contributed massively to their insane valuation.
    • LegitShady 5y ago
      Tesla pivoted to video only. They originally tried with radar as well. So any such statements by musk are already a pivot.
      • ra7 5y ago
        Their radar removal was baffling. There were rumors (perhaps Musk's tweets?) of Tesla investigating 4D imaging radars to replace their really old Continental radars, but they suddenly decided to remove it altogether. Many have attributed it to chip shortage and yet again Musk using vision-only as an excuse for removal.
        • 5y ago
• drawkbox 5y ago
  In the end I think self-driving regulations will require depth checking beyond computer vision as it can be tricked on any new situation. Depth checks using LiDAR are extremely efficient up to a football field away down to the direction someone is facing. RADAR is not as good but better than video/flat 2D depth detection though is limited by range, however it does work in weather where LiDAR doesn't and computer vision struggles. Autopilot and now FSD on Teslas doesn't have depth checking beyond visual/cameras. They removed the RADAR/sonar and have zero physical world depth checking currently. Tesla recently instead of adding LiDAR, they [just removed RADAR to rely on computer vision alone even more](https://www.cnbc.com/2021/05/25/tesla-ditching-radar-for-autopilot-in-model-3-model-y.html https://www.cnbc.com/2021/05/25/tesla-ditching-radar-for-aut...). Self-driving cars need cameras and physical depth checking sensors like LiDAR, or at least RADAR. Telsa has only cameras and some sensors but not for depth anymore, that is insane. Humans have essentially LiDAR like quick depth testing. Humans have hearing for RADAR like input. For autonomous units, depth may be actually MORE important than vision in many scenarios. Humans have inherent depth checking with 3D space, movement, sound, lighting, feel, atmosphere, air, pressure, situational awareness, etc that computer vision converted to 2D flat images for depth checking will never be able to replicate. A human can glance at a scene and know how far things are not just by vision but by how that vision changes with these distance inputs. Humans are able to detect 3D/2D imagery easily where it is all based on 2D with a camera. LiDAR is faster than humans at depth checking in the actual physical world not just from an image flattened. With just cameras, no LiDAR OR RADAR, depth can be fooled. Like this: [TESLA KEEPS “SLAMMING ON THE BRAKES” WHEN IT SEES STOP SIGN ON BILLBOARD](https://futurism.com/the-byte/tesla-slamming-brakes-sees-stop-sign-billboard https://futurism.com/the-byte/tesla-slamming-brakes-sees-sto...) Or like this: There is the [yellow light, Tesla thinking a Moon is a yellow light because Telsas have zero depth checking equipment now that they removed RADAR and refuse to integrate LiDAR](https://interestingengineering.com/moon-tricks-teslas-full-self-driving-into-thinking-it-is-a-yellow-light https://interestingengineering.com/moon-tricks-teslas-full-s...). LIDAR or humans have instant depth processing and can easily tell the sign is far away, cameras alone cannot. LiDAR and humans can sense changes in motion, cameras cannot and even RADAR struggles with dimension (frame to frame changes). LiDAR is better than humans on changes in motion, depth, seeing all around always, and much faster at all those things. [LiDAR vs. RADAR](https://www.fierceelectronics.com/components/lidar-vs-radar https://www.fierceelectronics.com/components/lidar-vs-radar) > Most autonomous vehicle manufacturers including Google, Uber, and Toyota rely heavily on the LiDAR systems to navigate the vehicle. The LiDAR sensors are often used to generate detailed maps of the immediate surroundings such as pedestrians, speed breakers, dividers, and other vehicles. Its ability to create a three-dimensional image is one of the reasons why most automakers are keenly interested in developing this technology with the sole exception of the famous automaker Tesla. Tesla's self-driving cars rely on RADAR technology as the primary sensor. > High-end LiDAR sensors can identify the details of a few centimeters at more than 100 meters. For example, Waymo's LiDAR system not only detects pedestrians but it can also tell which direction they’re facing. Thus, the autonomous vehicle can accurately predict where the pedestrian will walk. The high-level of accuracy also allows it to see details such as a cyclist waving to let you pass, two football fields away while driving at full speed with incredible accuracy. Waymo has also managed to cut the price of LiDAR sensors by almost 90% in the recent years. A single unit with a price tag of $75,000 a few years ago will now cost just $7,500, making this technology affordable. > However, this technology also comes with a few distinct disadvantages. The LiDAR system can readily detect objects located in the range of 30 meters to 200 meters. But, when it comes to identifying objects in the vicinity, the system is a big letdown. It works well in all light conditions, but the performance starts to dwindle in the snow, fog, rain, and dusty weather conditions. It also provides a poor optical recognition. That’s why, self-driving car manufacturers such as Google often use LIDAR along with secondary sensors such as cameras and ultrasonic sensors. > The RADAR system, on the other hand, is relatively less expensive. Cost is one of the reasons why Tesla has chosen this technology over LiDAR. It also works equally well in all weather conditions such as fog, rain, and snow, and dust. However, it is less angularly accurate than LiDAR as it loses the sight of the target vehicle on curves. It may get confused if multiple objects are placed very close to each other. For example, it may consider two small cars in the vicinity as one large vehicle and send wrong proximity signal. Unlike the LiDAR system, RADAR can determine relative traffic speed or the velocity of a moving object accurately using the Doppler frequency shift. > Though Tesla has been heavily criticized for using RADAR as the primary sensor, it has managed to improve the processing capabilities of its primary sensor allowing it to see through heavy rain, fog, dust, and even a car in front of it. However, besides the primary RADAR sensor, the new Tesla vehicles will also have 8 cameras, 12 ultrasonic sensors, and the new onboard computing system. In other words, both technologies work best when used in combination with cameras and ultrasonic sensors. LiDAR and depth detection will be needed, no matter how good the pure computer vision solutions get. The accidents with Teslas were the Autopilot running into large trucks with white trailers that blended with the sky so it just rammed into it thinking it was all sky. LiDAR would have been able to tell distance and dimension which would have solved those issues. [Even the most recent crash where the Tesla hit an overturned truck would have been not a problem with LiDAR](https://www.latimes.com/california/story/2021-05-16/tesla-driver-in-fatal-california-crash-had-post-videos-of-himself-in-vehicle https://www.latimes.com/california/story/2021-05-16/tesla-dr...). If you ask me sonar, radar and cameras are not enough, just cameras is dangerous. Eventually I think either Tesla will have to have all these or regulations will require LiDAR in addition to other tools like sonar/radar if desired and cameras/sensors of all current types and more. LiDAR when it is cheaper will get more points almost like Kinect and each iteration of that will be safer and more like how humans see. The point cloud tools on iPhone Pro/Max are a good example of how nice it is. Human distance detection is closer to LiDAR than RADAR. We can easily tell when something is far in the distance and to worry or not about it. We can easily detect the sky from a diesel trailer even when they are the same colors. That is the problem with RADAR only, it can be confused by those things due to detail and dimension especially on turns like the stop sign one is. We don't shoot out RADAR or lasers to check distance but we innately understand distance with just a glance not just from vision alone though. Humans can be tricked by distance but as we move the dimension and distance becomes more clear, that is exactly LiDARs best feature and RADARs/CV trouble spot, it isn't as good on turning or moving distance detection. LiDAR was built for that, that is why point clouds are easy to make with it as you move around. LiDAR and humans learn more as they move around or look around. RADAR can actually be a bit confused by that. LiDAR also has more resolution far away, it can see more detail far beyond human vision. I think in the end on self-driving cars we'll see BOTH LiDAR and RADAR but at least LiDAR in addition to computer vision, they both have pros and cons but LiDAR is by far better at quick distance checks for items further out. This stop sign would be no issue for LiDAR. It really just became economical in terms of using it so it will come down in price and I predict eventually Tesla will also have to use LiDAR in addition. [Here's an example of where RADAR/cameras were jumpy and caused an accident around the Tesla](https://youtu.be/BnbJvUwbewc?t=262 https://youtu.be/BnbJvUwbewc?t=262), it safely avoids it but causes traffic around to react and results in an accident. The Tesla changed lanes and then hit the brakes, the car behind was expecting it to keep going, then crash.... dangerous. With LiDAR this would not have been as blocky detection, it would be more precise and not such a dramatic slow down. Until Tesla has LiDAR it will continue to be confused with things like this: [TESLA AUTOPILOT MISTAKES MOON FOR YELLOW TRAFFIC LIGHT](https://futurism.com/the-byte/tesla-autopilot-mistakes-moon-traffic-light https://futurism.com/the-byte/tesla-autopilot-mistakes-moon-...) and this: [WATCH TESLA’S FULL SELF-DRIVING MODE STEER TOWARD ONCOMING HIGHWAY TRAFFIC](https://futurism.com/the-byte/watch-tesla-self-driving-steer-toward-oncoming-highway-traffic https://futurism.com/the-byte/watch-tesla-self-driving-steer...). [They are gonna want to fix FSD wanting to drive toward moving trains](https://twitter.com/TaylorOgan/status/1487080178010542085 https://twitter.com/TaylorOgan/status/1487080178010542085). In the end I bet future self-driving, when it is level 6, will have computer vision, LiDAR, RADAR and potentially more (data/maps/etc) to help navigate. [Tesla FSD has been adding more of data/maps in which is basically what they said they didn't need to do](https://twitter.com/WholeMarsBlog/status/1488428565347528707 https://twitter.com/WholeMarsBlog/status/1488428565347528707), so LiDAR will have to come along eventually. Proof of them [using maps data](https://twitter.com/IdiocracySpace/status/1488433509978939392 https://twitter.com/IdiocracySpace/status/148843350997893939...) and possibly previous driver data. LiDAR is extremely fast and accurate up to multiple football fields even determining which way a pedestrian is facing, with high fidelity. That is much better than a camera or computer vision. LiDAR can get many reads in the time you could do one complete CV pass. The best process is to do depth checks across the viewable area, then overly the results of the computer vision tick, then again check the differences and when it comes to depth, go with the LiDAR feedback as video can be wrong/tricked. This is probably how the cars that use LiDAR are doing it (Waymo/Cruise/etc), the equipment is also on the roof for better vision/coverage. Tesla is going to be massively behind when the regulations come down that self driving needs depth checks beyond CV. You can still base lots of the process on CV. However doing depth solely in CV can be tricked and uses massive amounts of processing power which ends up with faster usage of power. CV will always be limited in distance, dimension and depth to LiDAR and physical world detection/sensors. To think a Tesla can drive you without intervention or watching it closely, there will eventually be a distance confusion and it won't go well. The name Autopilot was better as it inferred like a plane where you still have to watch it, though planes are much further apart. The name Full Self Driving should be changed immediately even in beta, it is going to be ripe for lawsuits and problems. Tesla is trying to brute force self-driving and it will have some scary edge cases, always.
• LegitShady 5y ago
  In Lex fridmans interview with George Hotz, hots talks about why he thinks radar AI is a non starter and predicted that even though Tesla was still adamant about using their radar, they would eventually realize they only needed cameras. Hotz is the founder of comma.ai which is doing open source (I think?) Company.
  • KerrAvon 5y ago
    What were his reasons? Searching the web reveals lots of machismo and assorted hero worship, but no actual solid technical arguments. Nobody in the field seems to think a vision-only solution is practical, other than Tesla, who are also not providing solid technical arguments that I can find. This IEEE item seems to summarize the situation well. https://spectrum.ieee.org/tesla-places-big-bet-vision-only-self-driving https://spectrum.ieee.org/tesla-places-big-bet-vision-only-s...
    • LegitShady 5y ago
      It was a discussion about how such a system must function with all the different inputs vs the vision only model. If you have radar and lidar and vision, then you have at least three different specialist machine learning models running, and then another model running that takes their outputs and decides what the car is going to do. You may have even more than that, some doing specific tasks like localization. Neural nets and vision only is a more difficult but in the long run straightforward solution. The example he brought up was alphazero vs some other chess engine that has a rook engine, and a knight engine, etc. Basically he's backing the end to end neural network back approach over some kind of multi-sensor fusion. https://youtu.be/_L3gNaAVjQ4?t=3801 https://youtu.be/_L3gNaAVjQ4?t=3801
      • YZF 5y ago
        That argument doesn't make any sense though. Clearly radar + lidar + vision is a superset of vision only. It can perform as well as vision only if you disable the other two. So the claim is there is absolutely no scenario where the other systems can contribute which seems to be false. E.g. Tesla's cameras are blinded pointing straight on into the sun, the car even tells you the cameras are blinded. If the cameras are splashed with mud they'll also see nothing. Tesla's radar was able to see "through" some obstacles which the vision system can not (and you can see that in the traffic visualizations). Now how far do you want to fuse, do you just want to overlap the unique sensing abilities of each of those systems? How do you handle conflict when you're in the regions where all systems sense "equally" well. Sure, there's questions. But clearly having more data can't make things worse. Elon's argument that that's the way to go because that's how humans drive is just ridiculous. And I say this as a proud Model 3 owner (great car, will never ever be autonomous, I don't care). It doesn't pass the sniff test.
• catillac 5y ago
  Can someone explain whether there is a principled reason to not use all the sensors available and choose just cameras?
  • xiaolingxiao 5y ago
    From public information it's a matter of price and "appearance." No one who's half serious about understanding how the system work would use cameras alone, but remember of all the companies who's serious about putting self driving cars on the road, Tesla is the only one who designs, manufactures and sells cars. Incidentally, Tesla is also the only car company pushing camera only as a "solution" which again, it is not. All other outfits are tech pure plays, so their incentive is more geared towards a working system, because that's the only thing they can sell aside from the dream. If Tesla fails with a camera-only self driving car system, they can still sell cars. Source: used to work in robotics, all my classmates from grad school work or have worked at a self driving car company.
    • kzrdude 5y ago
      It sounds very stupid from their side to be stubborn, at least, that just means they have an existential risk to the whole company, if they don't get their fav solution to work.
  • jfoster 5y ago
    Think along the lines of: 1. What is necessary vs sufficient. 2. Processing power. 3. Power consumption. 4. Hardware cost. (even if may have decreased now, the cost of initiating the programme years ago) 5. Training cost / volume of data. The approach that Tesla is using balances all these things. I can't fully explain why it's so controversial, but I suspect this topic attracts folks from autonomous startups who are using very different approaches, people who repeat what they've heard elsewhere, and the usual anti-Tesla folk. If you want to know whether Tesla's approach can work, first realise that the sensor suites only help with the 'perception' part of the autonomy problem. Then watch some of the Tesla FSD videos on YouTube and check whether the visualisation seems accurate or not. It's certainly not 100% perfect yet, but it's clear to me that the perception part of the problem is mostly solved. The biggest remaining problems seem behavioural.
• justapassenger 5y ago
  > They and their VC backers are clearly betting on the concept that radars + lidar + imaging will be the ultimate successful solution in full self driving cars, as a completely opposite design and engineering philosophy from Tesla attempting to do "full self driving" with camera sensors and categorical rejection of lidar. Tesla's approach is a textbook case of premature optimization.
  • amacneil 5y ago
    Tesla's approach is a textbook case of differing constraints. Despite Elon's commentary, the reason Tesla does not use lidar is sensor cost (waymo/cruise cars probably have 250k+ worth of sensors on them), and reason Tesla does not use radar is supply chain.
    • justapassenger 5y ago
      Sensor cost is a lame excuse, especially coming from a company that's one of the leaders of EV world. Battery prices are decreasing, but sensors wouldn't? Tesla put constrain on themselves, because they wanted to sell product years before they existed, and they were super cheap on HW, to optimize their costs. They optimized their solution, before they even had a slightest idea what's needed to make it work.
      • emef 5y ago
        core to tesla's strategy is to do massive data collection from consumer-owned cars using beta software (and hardware, that the consumer pays for). that model is not compatible with expensive lidars, which contrary to some other comments in this thread, are still very expensive (just because the entry-level pucks are cheap, does not mean full lidar coverage is cheap). there is no way they could push $100k of sensors on consumers to build out their data collection pipeline. when tesla was first starting out, affordable lidar did not even exist so it's hard to call that a lame excuse. all that said, I'm still pessimistic about tesla's chances at making camera-only L4 work in any short time horizon. we will see if they pull it off, but it's such a severe disadvantage compared to fully-kitted competitors.
• hngpt2 5y ago
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