CyberTaxi FSD Training Cars in Austin

*let it grow* 🪴

Yea fsd/autopilot validation cars

What is that black hose like object coming out of the rear window?

Not scalable at all. And wow, so cameras aren’t enough without extensive LiDAR mapping? Refund please

They've had these rigs for a very long time. They have LIDAR and are used so they can measure their visual system against a ground truth. This has been reported quite a lot recently, so my guess is that they have a new revision of the occupancy network that they're verifying.

It’s used for calibrating the cameras and software. It’s not meant to be used for navigation.

It’s more than calibration. They’re fully mapping out the Robotaxi portion of the city with LiDAR before letting the camera-only cars loose on them. This implies that our cars won’t be able to do unsupervised FSD until they do similar training in our cities, which is not feasible to roll out nationwide and is not what they promised us. It’s why they are limited to a small area within Austin, not even the whole city. That’s why you see people saying “wow Robotaxi slows down at speed bumps!” when in reality the car just knows the speed bump is there already from the extensive training with additional sensors. It’s not generalized for camera-only like they claim.

I love the fact that the legacy MY’s are running naked Gemini’s.

Good eye…it looks like some custom pass through to get interior power (and whatever else) to the external devices

My point exactly in the other comment. Camera-only is not feasible for unsupervised FSD like they’ve claimed it is, unless they map out the whole area with LiDAR first. Our cars will not be able to do unsupervised FSD outside of areas where they have done this mapping. To me this is them admitting defeat on the camera-only generalized approach.

My 8 cameras with V13 work wonderfully.

Just saw one in san mateo California. Hopefully validating for this area

Agree totally

Have they mentioned how many trips have been taken so far on the current trial at all? It would be interesting to see the numbers.

Not wonderfully enough for unsupervised FSD sans LiDAR mapping according to them!

They do not release that kind of data. For Autopilot, FSD, or otherwise

I thought the lidar systems in their fleet were more to measure how accurate the network is, and allow it to be closer to ground truth in unmapped scenarios, so that it can be camera only. Kinda like verification the occupancy network sees things as they actually are every now and then in mapped areas for ground truth testing. Like verifying the data where they can so it'll work where they can't? But also it makes sense to check a lot when they're gonna do more stuff there, media outlets are on tesla like flies on a cow patty.

Does anybody think the legacy model Y would be able to be a robotaxi

You could be right, but it’s total speculation. No one has any idea if it’s mapping or verification-only.

Previously yes, but the fact that they’re doing it so extensively, specifically in the Robotaxi geofence, at this moment… tells another story.

They’re not mapping it. They’re verifying that camera-only system that you claim isn’t feasible is actually quite feasible.

> It’s more than calibration. They’re fully mapping out the Robotaxi portion of the city with LiDAR before letting the camera-only cars loose on them. And why do you say that? How do you know?

They aren't mapping the area with LiDAR, they're validating the software - something they've been doing for years.

That's exactly right. Anyone suggesting that it's mapping the surrounding area is incorrect.

Exactly. Camera only does work, sometimes. Every time? No. could it get there? Maybe. Humans can judge distance and do it with only two visual sensors and a Tesla has many more. Sone humans drive with only one good eye. I think a lot of people believe that FSD has to be flawless, but it only has to be better than the average human to be worth it to deploy en mass and remove humans from the equation. Insurance companies will love the less risk involved with insuring a AI vs ensuring the larger risk of humans. It's nearly at that point already according to non biased people like John carmack and 8-bit guy on YouTube

Looks like the camera system doesn't work as advertised. Lidar is needed.

Scale, timing, and location. They’re doing widespread LiDAR drives right before the Robotaxi pilot rollout, specifically in/around the geofence. Tbh it seems obvious to me… Remember the pre-mapped demo at the reveal? It’s that but bigger.

Hopefully they're releasing v14 soon, or at least 13.3

He doesn’t know. He pulled all of it out of his ass. There’s zero evidence that Tesla is pre mapping areas a la Waymo style.

Follow your username becuase you're so wrong you need to let it go.

FSD slows down for speed bumps for me and I'm not in a city Tesla has ever talked about deploying Cybercabs. Just sharing my data point.

Lol people still say this ?

Why else would they put a tower on all of the test cars and delay robo taxi and put towers on those with a test driver?

These cars are driving around running the vision system alongside LiDAR to collect training data. Simplifying massively, think of it as if the vision system says a wall is 10m away, and LiDAR measures it as 10.3m, then they have training data that can be used to improve the vision system. As they're driving they'll be collecting the output of the vision system's distance estimates its surroundings and training the underlying neural network against the LiDAR point cloud. They've been doing this from the outset.

You're clueless and have never used FSD.

With human driving, they can take over. Vision works, but crashes have already happened with robo. I get you are a fan but safety first.

I enjoy FSD, but it is not that. Any time you have to take over that would be a robo issue. It's not ready for prime time yet.

Yeah I’ve seen them around, literally every photo here was taken within 5 minutes on Congress Ave bridge. I left off two more Ys.

What’s that ?

I'd claim it needs to be better than the competition, not only better than humans, particularly under bad conditions — if they really want to dominate the market. Otherwise, as a customer, I'd definitely call the safer service.

They've been doing that for many years. Probably just some sort of validation.

I think I know what you're talking about. Originally, Waymo used LiDAR because GPS was poor quality. So to get around that, they would map an area with LiDAR so they could figure out where they were in physical space. Back then, that was the only way to do it. Now, the camera and visual models are so good, you can do the same thing without LiDAR.

You made a false claim in the context of this thread, I simply described what they're doing, and now you're off on some rant about me being a fan? Crashes have happened with LiDAR too. Waymo have had 833 crashes so far, obviously not all of them Waymo's fault just involving one of their vehicles, but I can't find a breakdown by blame. They've had 137 incidents so far this year, with one fatality, one serious injury, three moderate injuries, and 11 minor injuries. [Here is a video](https://www.reddit.com/r/SelfDrivingCars/comments/1h7wr4u/waymo_drives_straight_through_a_car_accident_scene/) of a Waymo with LiDAR driving through the middle of a crash. To borrow your parlance, I get that you're a hater, that you're here to throw shade at Tesla no matter what they do - but you are objectively and factually wrong to claim that *because* they collect test data using LiDAR that their vision system doesn't work as advertised and that LiDAR is needed on their production vehicles.

Wow.. yes, a lot of technological advances are happening. That doesn't mean anyone is ready yet. Again I get you are a fan, but it's not ready. Edit: I made an observation, you are on a rant for some reason.

Gemini are the wheels on the pre-Juniper Model Y and they’re running these without the wheel covers.

LiDAR says 'something' is 10.3m away, but has no idea what it is.

Lidar is only used for verification, just like in other vehicles. Radar and lidar are pretty dumb sensors that can tell you very precisely that 'something' is 5.4m away. They can't see what that thinhmg is, if it's a truck or a dumpster. Camera's do most of the work, lidar/radar are just verifying. If your Camera's with it's software is capable enough, you don't need verification.

They are not mapping the area out. They are using the extra sensors to verify what the camera is seeing and how accurately it is judging distance. Its just an additional training tool for the camera system and is one reason why the cameras are as good as they are.

So, is there no verification needed in whiteout snow or extreme fog? In central California, we have what's called pea soup. You can't see shit when the fog rolls in.

Where did I claim it's ready? Your observation wasn't based on what was in this thread. How did you conclude that the camera system doesn't work and LiDAR is needed when looking at test vehicles gathering training data?

Correct, nor can it read road signs, lane markings, etc. A working vision system is needed regardless. Some people think that needs to be supplemented with LiDAR, others think the vision system is enough on its own. Neither side has been proven diffinitively correct as yet.

I was the first comment, so I had nothing to observe. If the camera system was the only solution, they wouldn't need the other solutions to "train" on. Its been 10 years since next year.

LiDAR is about providing real time data at moments where the cameras can't and will never be able to do so. That's called redundancy and insure that in 100% of cases, the system will have enough good information to work properly.  A great example of lack of redundancy, in a way more regulated environment, was the 787 max of Boeing where a critical system (MCAS) was relying on the input of a single sensor (instead of 3) and lead to 2 major crashes.  It has really not much to do about GPS and mapping.

How to tell the world you don't know how AI/ML works without saying it

Statistically yes. However, realistically for actual full blown adoption we would want an AI performance that is orders of magnitude better, at least many standard deviations from average. That way, all the drivers with an actual skill that is +x STDs above average and most importantly those that **believe** they have that skill (which is going to be a lot of people), won't feel like they're downgrading. This is when we reach a critical adoption point and can actually absorb most of the cars under the self-driving umbrella - which in turn will yield a positive feedback loop of driving safety, due to a convergence in driving nature/patterns and in turn driver predictability and planability. This loop will just keep on increasing the capacity and "statistical" safety of the self-driving systems, as more and more STDs of "statistical" safety is added and above points are repeated/reinforced.

Apparently not. It's also not possible to verify in those situations using Lidar. LiDAR suffers from the same challenges camera's do which is the droplets in the air reflecting photons. That's the reason a Waymo pulls over even with moderate rain. Due to lens and software filtering camera's actually come ahead in these situations. The main thing lidar improves upon is accuracy.

> I was the first comment, so I had nothing to observe. You had the pictures that you're commenting on. If you're now claiming that you didn't even look at the pictures and just wanted to post about how terrible Tesla are then that makes your position look even worse. > If the camera system was the only solution, they wouldn't need the other solutions to "train" on That's a fundamental misunderstanding of how training neural networks functions. In simplistic terms you train a network by comparing its output with the output that it should have given, feeding the difference back through the neural net so that the weights between the neurons can be adjusted to move the network slightly closer to producing the right output. That process is repeated over and over with different inputs, different validated outputs, and fresh back propagations through the network, steadily improving the overall response of the network and moving it towards being "good enough". Taking the example of the vision system producing a depth field - they will capture a LiDAR point cloud of the location at the same time the video feed is captured. They'll then compare the neural network's calculated depth field against that produced by LiDAR, and use LiDAR data to improve the vision system. No one is claiming that LiDAR doesn't produce good depth data in the form of a point cloud. That's a given when in perfect conditions, so it provides excellent training data. Some people, it would appear yourself included, are claiming that a vision system can never be good enough at estimating that depth data for the task of driving a car. Tesla believe otherwise, and time will tell if they're right or not. > Its been 10 years since next year And? Is it taking longer than they estimated? Sure. But Tesla are operating at the edge of what is currently possible. It's not as if countless other companies have leapfrogged them and Tesla are being left in the dust with a solution that looks like it'll never work.

Ah thanks

Wonder if it has something to do with the new front bumper camera? Maybe they're going to utilize it soon and are validating it

So they still need additional specific training... Not what was advertised that vision only FSD will be able to just drive anywhere

Cybertruck too. No wheel covers.

Is that Gollum driving? *myyy preeecious*

carpenter soft soup fragile airport hard-to-find simplistic selective decide dinner *This post was mass deleted and anonymized with [Redact](https://redact.dev/home)*

But those aren’t Gemini’s.. 😉

I think your reply is great and covers the crux of the debate. It explains why people get trapped in a totally technical back-and-forth, when that’s not entirely the issue at-hand. **Is vision + compute _technically_ enough?** Yes — first principles says it must be; it’s how we drive **Can vision + compute perform superhuman and, thus, to the point where people will accept it (even if they’re applying an irrationally high standard)?** TBD — when is this standard even achieved? When no one can record a video clip of wonky behavior and share it online? Some statistical population data says so?

I don't really understand how someone can process facts the way you do. Do you really understand what you just said? Are you 15yo?

I thought the occupancy network was dead after the move to E2E? The occupancy network was important during the handcoding so you could navigate a 3d, reconstructed world, but with E2E it's just photons to control input. The car knows to avoid XYZ simply because training data has shown that's the most probable outcome.

Apparently the Cybertruck is flop. Might as well make them into taxis.

TBF they’ll make CyberTaxi XLs

I've looked into this and I don't believe they've gotten rid of the occupancy network. The end-to-end was the path prediction. So instead of having a whole bunch of C++ code figure out what the driving controls could be, they have a neural network figuring that out. I was hoping it would be as you described, but I can't find any evidence of it.

***Sone humans drive with only one good eye.*** I was born badly cross-eyed, and my brain wired itself based on that, and after I got the surgery (at a few months old) I found I do not have stereoscopic vision, and depth perception is really hard; it's very difficult for me to catch a ball, and stuff like pickleball is really hard. But I can drive ok, so I bet Tesla's Camera Vision would really improve upon my capabilities.

Explain like I'm 5 - if GPS is poor quality, even with their own maps, how does the car know exactly where it is without GPS?

I'm not sure that this is a more convincing argument than them using lidar alongside camera for proven validation of vision only performance against a lidar baseline before rollout. Even then, having a lidar scan of the environment isn't going to change the fact that the cars rolling out will not have lidar.

That’s a long way to say that you actually have no idea, and you’re just speculating. How do you know they aren’t just training on the local roads that they will expand the taxi service into? The same thing they’ve been doing for years.

It's fully integrated in the end to end network. You can literally see it still running when you go into parking mode. It's using the outputs from the internal occupancy network to drive those 3d visualizations.

The LIDAR may be part of the training, more than likely theyre using ground truth for teacher enforcing. Effectively training the visual model to improve it....this is essentially a win for all Tesla drivers who will consequentially receive the fruit of this labor on FSD (taking into account any hardware compute limitations).

Thats for the guild navigator....it feeds them the spice

Everyone they’ve been spotted in such numbers the next version of FSD has been close behind. Seeing it on the Cybertruck makes me incredibly happy because our version of FSD is lacking right now.

Dang, so no FSD through drive through confirmed. /s

BRING BACK LIDAR

I believe every company is doing that. E2E actually meant from sensor input to control, which I doubted from the beginning despite Musk's insistence.

Dont tell me you work for tesla without telling me. The point is alot of people paid for FSD and hw1 hw2 hw3 and hw4 people who paid are fucked and paid for something that still has not been in production and if you are 1, 2 or 3 you will never get it and possibly 4. Fsd is not happening "until next year"

> Dont tell me you work for tesla without telling me Can you not wrap your head around it being possible for someone to fundamentally disagree with you unless they have a bias? If you care to scroll back about a dozen or so posts in my comment history you'll see I tell someone else "Ha, thank you. It's frustrating as I've been founding and operating businesses for 25+ years, including selling my house when my daughter was a few weeks old to fund one particular venture." So no, I don't work for Tesla unless I have an elaborate plan to tell untruths to other people just to deceive you... > The point is alot of people paid for FSD and hw1 hw2 hw3 and hw4 people who paid are fucked and paid for something that still has not been in production and if you are 1, 2 or 3 you will never get it and possibly 4. That wasn't your original point, nor would it be relevant to a thread discussing some vehicles that are collecting test data. So your point is that you think Tesla sucks and you just want to tell everyone about it regardless of what they're discussing? > Fsd is not happening "until next year" So you don't think Tesla will ever solve it? Even though they've already had the first driverless car delivery and have soft launched the taxi service with a clear roadmap from rolling it out to an ever wider audience... If you're so confident why don't you go short Tesla stock and make a killing?

Pitot tube like the airplanes!

Can someone explain this validating thing. I thought the whole point was general purpose driving no need for mapping/validating etc.

Elon's argument has been that there could be a possible conflict between visual sensors and lidar and the AI model would have a tough time deciding which one is correct. In theory that sounds like a valid argument for only training with visual and cutting out lidar. I won't say he's wrong but we also know cutting out lidar is significantly cheaper.

Yeah, I’m familiar and not sure where I land on that one … Tesla uses lidar to validate their vision, so it seems (to me, anyways) like they’re implicitly acknowledging LiDAR is more trustable

Looks suspiciously like they're using Lidar to me

You got it, and maybe a data connection as well?

Dear Engineering dept. What will happen in a scenario where a gang uses another vehicle or obstacle to force a car to stop, subsequently robbing (or worse) the occupants.