BYD's cheapest electric cars to have Lidar self-driving tech (opens in new tab)

To me any kind of driving is torture. I don't want the responsibility, the risk, the chance of fines if I miss a speed sign somewhere. And if my car could self drive I could spend the time usefully instead of wasting it on driving. It would be amazing.

Right now I don't even have a car but for getting around outside of the city it's difficult sometimes.

Unfortunately in my region highway traffic is quite congested, and so called "adaptive cruise control" is a game changer. I find it reduces fatigue by a lot. Usually the trucks are all cruising at the speed limit and I just hang with them. I only change lanes if they slow down or there's an obstruction etc.

Driving in fog is the number one reason I want lidar looking out.

A combination of cameras, lidar, ridar, ultrasonic fused together have a strong sense of perception since they fill in each other's gaps. (short, long, different spectrums of electro-magnetic spectrum / sound).

The good news is they're all commodity hardware prices now.

Tesla removing radar and parking ultrasonic sensors was a self own. Computer vision inference is pretty bad when all the camera sees is a while wall when backing up.

Fog - Radar will perceive the car. Multi car crash, long range radar picks it up.

Bright glare from sun, lidar picks it up. Lidar misses something, camera picks it up.

Waymo has the correct approach on perception. Jam with sensor so they have superhuman vision of environment around.

Do you always get good wifi at a level of consistency with which you'd trust your life?

> camera+LIDAR

It's like having 2 pilots instead of 1 pilot. If one pilot is unexpectedly defective (has a heart attack mid-flight), you still have the other pilot. Some errors between the 2 pilots aren't uncorrelated of course, but many of them are. So the chance of an at-fault crash goes from p and approaches p^2 in the best case. That's an unintuitively large improvement. Many laypeople's gut instinct would be more like p -> p/2 improvement from having 2 pilots (or 2 data streams in the case of camera+LIDAR).

In the camera+LIDAR case, you conceptually require AND(x.ok for all x) before you accelerate. If only one of those systems says there's a white truck in front of you, then you hit the brakes, instead of requiring both of them to flag it. False negatives are what you're trying to avoid because the confusion matrix shouldn't be equally weighted given the additional downside of a catastrophic crash. That's where two somewhat independent data streams becomes so powerful at reducing crashes, you really benefit from those ~uncorrelated errors.

I was responding to the parent who said if you had to make a choice between lidar and vision, you'd pick lidar.

I know there are theoretical and semi-practical ways of reading those indicators with features that are correlated with the visual data, for example thermoplastic line markings create a small bump that sufficiently advanced lidar can detect. However, while I'm not a lidar expert, I don't believe using a completely different physical mechanism to read that data will be reliable. It will surely inevitably lead to situations where a human detects something that a lidar doesn't, and vice versa, just due to fundamental differences in how the two mechanisms work.

For example, you could imagine a situation where the white lane divider thermoplastic markings on a road has been masked over with black paint and new lane markings have been painted on - but lidar will still detect the bump as a stronger signal than the new paint markings.

Ideally while humans and self driving coexist on the same roads, we need to do our best to keep the behaviour of the sensors to be as close to how a human would interpret the conditions. Where human driving is no longer a concern, lidar could potentially be a better option for the primary sensor.

Everyone is missing the point, including Karpathy which is the most surprising because he is supposed to be one of the smart ones.

The focus shouldn't be on which sensor to use. If you are going to use humans as examples, just take the time to think how a human drives. We can drive with one eye. We can drive with a screen instead of a windshield. We can drive with a wiremesh representation of the world. We also use audio signals quite a bit when when driving as well.

The way to build a self driving suite is start with the software that builds your representation of the world first. Then any sensor you add in is a fairly trivial problem of sensor fusion + Kalman filtering. That way, as certain tech gets cheaper or better or more expensive and worse, you can just easily swap in what you need to achieve x degree of accuracy.

Don't ultimately even the ones which are vision + LIDAR ultimately have to choose priority in terms of one or the other for "What do you do if LIDAR says it is blocked and sight says it is clear' or visa-versa?" Trying to handle edge-cases where say LIDAR thinks that sprinker mist is a solid object and to swerve to avoid it and say vision which thinks that an optical illusion is a real path and not a brick wall.

Since the current traffic infrastructure was built for human drivers with vision, you’ll probably need some form of vision to navigate today’s roads. The only way I could picture lidar only working would be on a road system specially made for machine driving.

Not that I'm aware of, but I was referring to the claim in the parent post that if you had to choose it would be insane to choose vision over LIDAR.

Roombas

Because making boring industrial machinery doesn't sustain a PE ratio of about 300. Only promising the world does that.

> why not simply do vertical integration and build your own robot arms?

Robot arms are neither a low-volume unique/high-cost market (SpaceX), nor a high-volume/high-margin business (Tesla). On top of that it's already a quite crowded space.

I think there’s room for both points of view here. Going all in on visual processing means you can use it anywhere a person can go in any other technology, Optimus robots are just one example.

And he’s not wrong that roads and driving laws are all built around human visual processing.

The recent example of a power outage in SF where lidar powered Waymo’s all stopped working when the traffic lights were out and Tesla self driving continued operating normally makes a good case for the approach.

I wonder how much of their trouble comes from other failures in their plan (avoiding the use of pre-made maps and single city taxi services in favor of a system intended to drive in unseen cities) vs how much comes from vision. There are concerning failure modes from vision alone but it’s not clear that’s actually the reason for the failure. Waymo built an expensive safe system that is a taxi first and can only operate on certain areas, and then they ran reps on those areas for a decade.

Tesla specifically decided not to use the taxi-first approach, which does make sense since they want to sell cars. One of the first major failures of their approach was to start selling pre-orders for self driving. If they hadn’t, they would not have needed to promise it would work everywhere, and could have pivoted to single city taxi services like the other companies, or added lidar.

But certainly it all came from Musk’s hubris, first to set out to solve the self driving in all conditions using only vision, and then to start selling it before it was done, making it difficult to change paths once so much had been promised.

> And if he still doesn’t realize and admit he is wrong then he is just plain dumb.

The absolute genius made sure that he can't back out without making it bleedingly obvious that old cars can never be upgraded for a LIDAR-based stack. Right now he's avoiding a company-killing class action suit by stalling, hoping people will get rid of HW3 cars, (and you can add HW4 cars soon too) and pretending that those cars will be updated, but if you also need to have LIDAR sensors, you're massively screwed.

> The ways in which Musk dug himself in when experts predicted this exact scenario confirmed to me he was not as smart as some people think he was.

History is replete with smart people making bad decisions. Someone can be exceptionally smart (in some domains) and have made a bad decision.

> He seemed to have drank his own koolaid back then.

Indeed; but he was on a run of success, based on repeatedly succeeding deliberately against established expertise, so I imagine that Koolaid was pretty compelling.

> The ways in which Musk dug himself in when experts predicted

This had happened a load of times with him. It seemed to ramp up around paedo sub, and I wonder what went on with him at that time.

To be frank, no one had a crystal ball back then, and stuff could go either way with uncertainty in both hardware and software capabilities. Sure Lidars were better even back then, but the bet was on catching up on them.

I hate Elon's personality and political activity as much as anyone, but it is clear from technical PoV that he did logical things. Actually, the fact that he was mistaken and still managed to not bankrupt Tesla is saying something about his skills.

Musk has for a long time now been convinced that all problems in this space are solvable via vision.

Same deal with his comments about how all anti-air military capability will be dominated by optical sensors.

Will there be major difference in ride experience when you take a Waymo vs Robotaxi?

Why is it preferable to wait for people to die and then sue the company instead of banning it in the first place?

> if company sells self driving, they are also taking full liability for any damages of this system

This is basically what we have (for reasonable definitions of full).

That's a legal non-starter for all car companies. They would be made liable for every car incident where self-driving vehicles were spotted in close vicinity, independently of the suit being legit. A complete nightmare and totally unrelated to the tech. Makes would spend more time and tech clearing their asses in court than building safe cars.

That strikes me as a weak argument. We have vehicles with legs, but wheels are just better, practically speaking.

The argument is that humans provide a proof-of-concept that vision + neural net can drive a car, because (for some reason) some people doubt this is possible. However there's no need for a "proof of concept" that mechanical legs can be built, because everyone already know that building mechanical legs is possible.

There’s no such thing as biological LiDAR.

What proportion is camera data and what is LIDAR?

Must be solved problem and something you should buy already? Right?

Flashing lights over rural intersections often do that. There is only one color there (yellow or red), but position is not a signal

Have you driven in America? We have the craziest lights you've ever seen. And that's just in my state

How about turn signal vs brake lights?

You can't do that though. Someone will not wear it - and they shouldn't have to.

Or instead of reinventing the world you could just use cameras

Camera's are not the issue, they are dirt cheap. Its the amount of progressing power to combine that output. You can put 360 degree camera's on your car like BYD does, and have Lidar. But you simply use the lidar for the heavy lifting, and use a more lighter model for basic image recognition like: lines on the road/speed plates/etc ...

The problem with Tesla is, that they need to combine the outputs of those camera's into a 3d view, what takes a LOT more processing power to judge distances. As in needing more heavy models > more GPU power, more memory needed etc. And still has issues like a low handing sun + white truck = lets ram into that because we do not see it.

And the more edge cases you try to filter out with cameras only setups, the more your GPU power needs increase! As a programmer, you can make something darn efficient but its those edge cases that can really hurt your programs efficiency. And its not uncommon to get 5 to 10x performance drops, ... Now imagine that with LLM image recognition models.

Tesla's camera only approach works great ... under ideal situations. The issue is those edge cases and not ideal situations. Lidar deals with a ton of edge cases and removes a lot of the progressing needed for ideal situations.

  >I'd love to take on this challenge: the article they linked shows the cost add for LIDAR (+$130)

The article claims that, but when you actually try to follow the source it fails the fact check.

https://news.ycombinator.com/item?id=46583727

Would be nice if you had been able to take it on, but as you say you don't have the data, so it's compared to nothing.

The issue isn't just the cost of the lidar units off the shelf. You have to install the sensors on the car. Modifications like that at the scale that Waymo does them (they still have less than 10K cars) are not automated and probably cost almost as much as the price of the car itself. BYD is getting around this by including them in a mass produced car, so their cost per unit is closer to the $130 off the shelf price. This is the winning combination IMO.

Tesla uses their own chips. Chips which you can’t skip by using lidar because you still need to make decisions based on vision. A sparse distance cloud is not enough

Jaguar only started using a synchromesh gearbox in the E-Type in '65 or '66 (Series II) - that's forty years after the Austin. I have no idea why the British love to abuse themselves.

Last week I saw some old Rolls Royce that I absolutely could not guess even the decade of. The carriage looked 1930s but the interior looked 1950s - until I noticed what might have been spark advance levers on the steering wheel. It's a super luxury vehicle with super conservative styling, so I really don't know if it had a luxury interior for it's time or a classic exterior for it's time.

Could you even manufacture Austin 7 at scale today for less than a Seagull?

3.3 is pretty quick compared to 13. Its quicker than the 0-30 I listed above.

Maybe you don't 0-60 often, but 0-30 has to be a bit more common?

Those Teslas in Australia are Chinese made too of course as are the majority of Teslas globally. USA made really doesn’t exist at all in Australia. It’s merely USA branded. Even the Ford Ranger that’s sold in Australia is made in Thailand.

How’s the charging infrastructure these days?

Don't Americans like big pickup trucks? Nobody else really drives those in large numbers.

Forever is a long time.

Once FSD, we will make rules about the software that will have the effect of excluding Chinese companies. I seriously doubt that I'll see Chinese cars here in my lifetime.

Absolutely. But this has an extra layer of urgency. Their entire goal is to be able to remotely turn off all of our infrastructure, which is handy leverage if you're looking to do things like invading a certain island nation.

American capitalists are fans of inbreeding...

American oligarchs won't put up with any competition.

By what metric? In terms of deaths, injuries, and crashes per mile their Full Self Driving at least an order of magnitude behind Waymo

I've struggled with this over the years, but think we can call it at this point: Waymo is definitely better.

Just too much real world data.

(i.e. scaled paid service, no drivers, multiple cities, for 1 year+)

That’s not true at all. Tesla taxis aren’t even close to Waymo’s capabilities.

I was just thinking about this on my 60 mile FSD driver I just finished. Basically inevitable that I would shortly go HN or reddit and read how FSD doesn't work.

FSD is here, it wasn't 3 or 4 years ago when I first bought a Tesla, but today it's incredible.

I hadn't heard that criticism. You can get multiple Waymos near each other without them crashing into things.

I am just some schmoe, but optics alone can be easily spoofed as any fan of the Wile E. Coyote has known for decades. [0]

What's crazy to me is that anyone would think that anything short of ASI could take image based world understanding to true FSD. Tesla tried to replicate human response, ~"because humans only have eyes" but largely without even stereoscopic vision, ffs.

[0] https://www.youtube.com/watch?v=IQJL3htsDyQ

Why isn’t the solution a combination of both?

everyone uses cellphone that transmit on the same frequency. they don't seem to cause interference. once enough lidar enters real word use. there will be regulation to make them work with each other.

Feel free to live in your cocoon, I have owned several euro cars, including e36 m3. Now own BYD Dolphin and Shark, the European car industry is history mate.

However LIDAR safety is currently mostly evaluated on the assumption of a single LIDAR being present. If LIDAR becomes common, with multiple systems per vehicle, the probability of multiple LIDAR beams of different LIDARs hitting your eye at the same time goes up

There have been reports of lidar damaging camera sensors. If it can damage sensors, it can damage retina. And unlike the sun, it's not visible. Someone could stare straight into it for a good while and not realize.

It's also typically at a wavelength that has lower risk to human eyes (ie near infrared).

Laser eye safety risk is very measurable and well classified.

You label the recordings that involve a crash, and use the lidar to avoid doing the same.