This was in California's central valley where it can get very foggy making it very hard to see traffic until it was almost in the intersection.
It was a quiet rural area though and by opening the windows on both sides and turning off the radio I could hear traffic quite a bit before I could see it. I'd sit at the stop listening until I'd heard a car or two go by to be sure that it was quiet enough that I could hear them. Once I'd calibrated my senses to that day's current conditions I was able to make the turn.
A better example would probably be hearing emergency sirens before there was any line of sight to the emergency vehicle.
It won't be a retrofit for older cars, which tells me current owners won't get to experience that next generation on FSD which will be possible.
I never bought mine (Ryzen '22 LR3 with earlier gen radar, now disabled, plus USS - still in use fortunately) for the FSD anyway so I don't mind. I won't blame those who might do though! (This is presently all speculation/rumours until officially confirmed).
Quiet vehicles should emit a peace cry, and I should look before I rocket.
Having fake noise just encourages pedestrians to keep looking at their phones and not use their eyes when crossing roads or cycle lanes and they can injure themselves or others by doing that.
Also, there's far too much noise in busy areas as it is, so it seems unhelpful to deliberately add extra noise to the environment.
They turn off over ~18MPH, though. After that, tire noise is much louder. As loud as an ICE car.
So, realistically, you’d hear a Prius if it’s going normal road speeds.
Side note: I wish the sound was more pleasant. When multiple cars are moving in a lot I call it the “choir of the damned”. They’re also louder than ICE cars and that’s kinda lame, we moved backwards WRT noise.
Are you saying the typical EVs you hear are _louder_ than ICE cars where you live?
As to the pleasantness of the noise - yeah, that seems to be a manufacturer's choice, or perhaps even driver choice? And let's hope just like annoying ring-tones of years past that the current selection dies out soon...
ICE cars are pretty quiet where I live. Either that or there is so much ambient noise that I've lost some of my hearing but either way I don't hear much of an engine noise with recent cars.
I don't know the people driving these cars well; perhaps they modded them (seems unlikely, given the neighborhood), or perhaps they're old enough to have escaped new requirements; regardless - they're too quiet here in my sample size of 1 neighborhood in NL.
Some have figured out how to disable it completely (just pulling the noisemaker causes a fault code to trigger) but quieting it down to roughly the volume of an ICE seems more reasonable to me.
Irrespective of the volume it is remarkable why any car designer thought that this was the right _kind_ of noise for the car to emit. Somebody chose that soundtrack, and you kind of have to wonder why...
Just when significantly cutting noise pollution from motor vehicles in urban areas is finally within our grasp we toss it away by forcing them to make stupid and annoying UFO noises on the grounds of nebulous safety concerns.
There were any number of ways of solving this that would have been less annoying and better for peoples' health[0].
For one thing, most people are able to use their eyes and will learn soon enough that EVs don't make much noise at low speeds and will keep an eye out for them. How do I know this? I live in Cambridge, UK, which is brimming with cyclists. They don't make much noise either, but you learn to look out for them (and very quickly too).
And for those who are partially sighted or blind some sort of warning device + appropriate signal could no doubt have been engineered and legislated.
But, no, we've gone for stupid noises instead.
[0] We now, of course, know that noise pollution does in fact cause health issues and, I'd argue, these outweigh the safety argument.
Check out: https://youtu.be/CTV-wwszGw8?t=815
What do you have in mind? I can’t think of anything as effective as sound—the blind person needs no special hardware to perceive it, and it can be easily spatially localized.
Noise pollution from ie ambulance, sports car, basically any motorbike, old car, trucks and so on is much much bigger. Where is your outrage for those?
And no, noise pollution from these cars discussed is not causing massive health issues that outweigh people getting maimed and killed by them, thats just your personal preferences (like not owning a car because you are young without a family etc) you would like to push on whole society for whatever personal reasons.
Maybe his personal reason is that he's absolutely capable of getting out of the way of a car, but he doesn't like noise. That's a reasonable preference. If you absolutely can't guarantee that a kid ends up under a car without the noise, fine, but I doubt that's true.
Sure, we dont live on this planet alone, but that seems like it's more justification for not intentionally making our shared space miserable, not less.
I've heard that some EV drivers turn off the sound because it annoys them. They are potentially setting themselves up for a lifetime of remorse.
Before this a Prius or any modern car would be dead silent at a stop because of stop-start technology. And even those small 1.6L don't make that much noise when idling.
Now you hear all these cars making their high-pitched UFO sound. And it is VERY irritating.
Presumably this intersection is at high enough speed on the cross traffic that it's the road noise tzs is listening for, not engine noise.
- A failure by Tesla to view the system that they are developing as what it really is - a physical safety-critical system and not "an AI". Those two are distinct systems as, with a physical safety-critical systems, the totality of the systems safety components cannot be fully expressed in software - neither initially nor continuously.
- To build on that point, Tesla is not allowing the Operational Design Domain (ODD) via a robust, well-maintained validation process determine the vehicle hardware as the ODD demands it to be. Instead, Tesla is trying to "front run" it (ignore the demands of the ODD) by largely focusing on hardware costs. The tension from failing to recognize that is why Tesla, in part, has a long history of being forced to (somewhat clandestinely) change the relevant sensor and compute hardware on their vehicles while promising to "solve FSD" (whatever that means) by the end of every year since around 2015 or so.
But what is AI? If it's just "artificial intelligence", it effectively includes all programming with if/then logic gates based on program input.
And? You think that is the totality of a physical safety critical system?
I can see how it appears to intelligent, but it lacks reasoning, creativity, and critical thinking.
It requires creativity to recognize the rules of the game as “try to be the first to reach the ball”, to recognize that the thrower may not have time to carefully aim, and that the others might chase the ball regardless of its location. Only if all three of those creative leaps are made, then logical deduction can take over to conclude “if the ball goes in front of me, stop before a kid does the same”.
And that’s not even getting into cases where you conditionally act like there’s a stop sign. The city of Houghton,MI has major streets along the side of a hill, and minor streets going up and down the hill. Every winter, sand is put down for traction, and every spring it is cleaned away. If there’s a late-season snowstorm after the spring cleaning, cars going downhill on the minor streets physically cannot stop, so everybody on the major streets looks uphill before crossing.
Short of location-dependent fine-tuned models, I’m not sure how machine learning could replicate the logic of “if snowy in late spring, grant right-of-way to cars headed downhill”.
Poor, poor Tesla cameras freak out as soon as the sunshine is too bright or there's snow or rain or ice or mud in the way. You'd think if they're going to rely on vision, every camera mounted on the car would have a way to "squint" in blinding-light conditions, or "wipe" the lens or something when smudges, rain, snow, ice, mud, or bug-splat blocks the view. But then, Tesla is insanely cheap, and all that would require parts, and that would impact margins, and that would impact stock price, and so, this is why we can't have nice things ....
Current self driving systems sometimes fail in perfect weather conditions on correctly marked, empty roads. There's a long road ahead if it's supposed to actually work in the real world.
It doesn't need to be perfect, it just needs to be better than humans.
All the sources I'm able to find say there are no cameras in existence that are as good as human vision. Human vision is quite good and adaptive to real world conditions of all sorts.
The reason we invented machines in the first place is because they're significantly better and more reliable than humans.
They go the boring path. Work together with regulators. Prove to them that whatever they are doing is actually save to use. Don’t oversell to their customers.
They go the way of building and retaining trust - with customers and regulation bodies.
Human vision isn't that perfect for driving when it's looking at a mobile phone.
https://e2e.ti.com/blogs_/b/analogwire/posts/ultrasonic-lens...
You could emulate the properties of blinking using piezoelectric transducers.
That said, Tesla was never in a position to use LiDAR because it has generally been extremely expensive. Solid state lidars are supposedly now hitting low volume testing for 2025 production years. Tesla is a mass manufacturer not a self driving start up, so there was never really an option for them to offer LiDAR without an extremely expensive self driving package.
One thing however that was obviously wrong was Elon’s promises, which were extremely misleading and helped build his fortune thanks to the misunderstanding. (Assuming this inflated stock values)
With solid state LiDAR supposedly becoming available for $500 in the next two years (a promise we have heard since 2016 but one that seems possibly to finally be coming true) we may never end up seeing if Tesla could have ever done it with pure vision - they could go with solid state LiDAR for forward facing driving in the next few years.
That said, over promising is going well for them. Perhaps they will just keep doing that.
Installing the LiDAR unit in the front bumper would require replacing the entire existing front bumpers since there's no handy fake grille or whatever you can pop out and replace. You'll also have to paint the bumpers to match and blend onto surrounding panels since these cars have been in the sun long enough that a fresh-from-the-factory bumper will have an obvious color mismatch. If you don't, you'll have pissed off car owners to deal with and, in all likelihood, another class-action suit.
A roof-mount avoids that, but has its own issues. You'll needs techs to drill a freaking hole in the roof, mount the LiDAR unit, hope that they manage to seal the penetration well enough that water won't leak into the car, and then run cables through the interior. A whole hell of a lot of cars will leak, even if the work is performed to spec, so you'll have extend warranty coverage to deal with it. Plus, you've now got an ugly box on the roof that may or may not match the paint properly, whereas presumably the new cars will at least integrate the unit's lines into the body panels so it's not quite as obvious. The same thing goes sticking it on the hood. That's to say nothing of any hardware replacements and the fiddly bits that'll be necessary for refits.
Tesla of course claims that the HW3 cars will still get FSD at some point, but unless they somehow figure out how to bend light, that blind spot will continue to be an issue on older cars.
The fact that some early HW4 units will ship with the updated camera suite but not the Radar only further adds to my point that some users are going to be left with inferior sensing systems despite having paid the same $10k for FSD as everyone else. The whole "radar will be used to train and improve the vision" argument is just nonsense made up by Elon & Tesla fans. A properly functioning radar camera sensor fusion system will be superior in every way to a camera only solution. And there will be 0 Tesla's that actually achieve "full self driving" (ie. you going to sleep in the back-seat and waking up at your destination) until Tesla adds things like a cleaning system to their existing camera solution for example. The hardware is simply inadequate.
I'm saying that, as we see, HW4 and radar are two distinct hardware configurations: saying that there will be a large sore spot because HW4 cars have radar is objectively false as not all of them do.
The fact that HW4 and radar are separate configurations by name is not important. HW3 is also included in the mix (you can buy FSD on it) and it has totally different camera placement. So radar aside there’s still a difference in the sensor suite.
People who paid $10k and were promised “FSD” and future hardware upgrades have every right to be pissed off about this.
The sensor costs $125 on eBay.
https://www.ebay.com/itm/175646053526?mkcid=16&mkevt=1&mkrid...
Honda says it’s millimeter wave.
https://techinfo.honda.com/rjanisis/pubs/web/docs/AJA15434.P...
Our Odyssey uses a combination of multiple radar sensors and a camera to provide excellent sensing. From what I have read, millimeter wave is best of both worlds between LiDAR and Radar.
https://www.engineering.com/ElectronicsDesign/ElectronicsDes...
LiDAR doesn’t seem practical.
I'm wondering why there isn't a law firm that wants to make a fortune by starting a class action suit.
So currently the vision stack is not greatly holding them back.
While our eyes can do that pretty reliable, we are organics and get tired - how many hours one can drive until this becomes almost imposible? I had a situation where I would hallucinate and and start believing something is in the street do I did a full stop - nothing happened, but was quite intense. Imagine the other way around - not stopping and hitting something.
A normal radar + some low level ASIC programming would do that without geting tired. My Audi from 2014 is quite good at that and I actually rely on this feature all the time.
Updates are happening around once a month and the decision making is getting noticeably better.
The full system for humans is “vision + brain” and for self-driving its “sensors + planner”.
The Waymo/Cruise philosophy is that since we don’t know how to make the planner human-brain-level, we should shift as much of the load as possible to the sensors, where we have the ability to use things that humans don’t have, like lidar and radar.
To me, Tesla FSD going vision-only is a bet on the progress of AI planning models. If the planner reaches a human-equivalent level, then human-equivalent sensors are fine. Time will tell if this is a good bet, but so far it’s not.
I’m fairly certain that people would drive more safely in GTA if their life was literally at stake.
I thought their argument was a little more like “since roads are designed for human vision, we should take a vision-based approach, too”.
Not saying it’s the right idea, just that’s how I thought they had put it.
https://neurosciencenews.com/peripheral-vision-brain-illusio...
Actually, my understanding is that the depth perception induced by binocular vision is relevant only within a relatively short range (like, single-digit number of feet away), which makes it relatively useless for long-distance depth perception needed for driving.
So it's not useless for e.g. pulling into a parking spot or steering around a close vehicle.
(I'm crosseyed and don't benefit from binocular depth cues. For the most part I do alright, though rarely I'm comically off when someone throws me a ball or I'm picking up something close to me).
Most of our depth perception isn't from stereopsis or other binocular cues.
Lidar has since dropped in price by a lot, an order of magnitude or more.
- why would the goal be "the same level or performance as humans" ?
For context, some towns are actively removing cars from whole areas not just for pollution impact but also for pedestrian safety. Moral issues aside, the status quo is just not enough, it needs to be way better.
- achieving the same level as humans being possible in theory doesn't mean we'll get there in practice.
Having enough hardware to realize something doesn't help if the software is not up to the task. And assuming they "just" solve the software issue could be like assuming 18th century people would "just" discover relativity.
Software becoming as good as human in video processing just feels like a "general AI is around the corner" kind of expectation.
This is what I mean with the last part of my argument. Lidar is supposedly an extremely thorough 3d depth map hopefully capturing at hundreds or thousands of FPS. But even if you have this data, the actual bulk of the problem with current self-driving isn't solved, that being the "business logic" for how to navigate the world smoothly and efficiently and to 'communicate' with other road users.
The result is subpar food because most recipes have a 1% problem called “seasoning”.
The “seasoning” of driving — the completely unpredictable and intuiting 1% of situations you find yourself behind the wheel where you just have to draw on your intuition and gut instinct — are the reason we need nothing short of AGI for _completely_ self driving vehicles.
I do think, though, trucking is ripe for AI disruption.
It's possible that the richest person on Earth is more concerned with doing good slash achieving his goals vs obtaining more currency/profit, which it would seem would have little to no marginal utility to him.
They are all, in the terminology, presently "default dead" until they figure it out.
Now, all of these things except the last one have some representation through an electronic or electromechanical sensor, but gluing them all together into what it takes to deal effectively with the intersection of vehicle dynamics and environmental dynamics is very hard.
Indeed, but humans also have an incentive to drive well, embodied by local traffic police and local laws, and even before passing their driving test they're made aware of the penalties for not driving well (which, let's remind ourselves, range from "mild ticking off"/"pay $$$" through "forfeit driving licence for a time" all the way to "forfeit liberty for a time")
Where are these incentives for self-driving algorithms?
If your algo breaks the law to a sufficient level, is someone(something?) prevented from driving for a time? Is that really going to be just that one vehicle, or should it be all vehicles with that same algo? If something really bad happens, who is charged; in the worst case, who might end up going to jail?
We all know CEOs tend to believe "this time it's different", that they're special, and that the annoying rulebook is to be viewed as guidance at best. VW/Martin Winterkorn, anyone?
Surely the equivalent is the reward during training?
> If your algo breaks the law to a sufficient level, is someone(something?) prevented from driving for a time? Is that really going to be just that one vehicle, or should it be all vehicles with that same algo? If something really bad happens, who is charged; in the worst case, who might end up going to jail?
Personal opinion:
Algorithm should learn from fleet and should be shared by fleet; therefore all accidents should be treated like aircraft crashes and investigated extremely thoroughly with a goal of eliminating root cause.
If that cause was CEO demanding corners be cut to boost shareholder value then jail them; if it's that the algorithm had, say, never seen a flying shark drone[0] before, and misclassified it as a something it needed to take evasive manoeuvres to avoid and that led to a crash, then perhaps not (except anything I suggest probably should be in their list of things to check for, so even then perhaps it would still be a CEO-at-fault example…)
[0] https://www.amazon.com/RiToEasysports-Control-Inflated-Infla...
Surely the counter-example to when a self-driving vehicle drives straight into a stationary fire truck?[0]
If a human driver did this more than once (and lived to tell the tale!) - yet had no explanation other than "Of course I saw it, but I wasn't sure what it was and didn't realise I needed to avoid hitting it it <shrug>" - wouldn't they lose their driving licence fairly quickly?
[0] https://www.google.com/search?q=tesla+stationary+fire+truck
You asked for the incentives for AI; the equivalent isn't the same as for humans.
The nature of the AI doesn't include a concept of prison or licensing, so it can't be threatened with it, for the same reason I can't threaten a human driver with Af'nek-leigh D'Och entRah'negh.
I can however 'punish' (air-quotes necessary because it might not feel like anything) an AI by altering the weights and biases of its network — once done, it then thinks differently.
Don't anthropomorphise it, that's a category error.
Also, the field of "how does it even?" is tiny, which is itself a reason to not grant them control of vehicles, but that's a separate issue.
There certainly should be incentives for the humans creating an AI, though.
> Don't anthropomorphise it, that's a category error.
Volkswagen [human!] engineers created the illegal defeat devices in Dieselgate, under the supervision of their [human!] managers. The device is illegal, we punish the humans in charge when laws are broken, not the devices themselves. It should be the same with AI.
If this means software engineering becomes a field where you need mandatory liability insurance to work on AI, is that a bad thing?
In the glorious words of Stelios Haji-Ioannou, "If you think safety is expensive, try [having] an accident"
The proper argument is “humans do driving with ~only vision -> roads are therefore universally designed and built to be driven via by vision -> computers should do driving with only vision”. It is essentially a standards-based argument: since vision is the universal standard for driving, computers must be able to drive using just vision.
So vision is always going to be the core of self-driving. Why not augment with LIDAR anyway?
Well, in situations where vision and LIDAR are both right, you didn’t need LIDAR; in situations where vision is right and LIDAR is wrong, you didn’t need LIDAR and it potentially made you worse off; in situations where vision is wrong and LIDAR is right, you need to spend more on improving your vision; and in situations where both vision and LIDAR are wrong, you need to spend more on improving both, but improving vision is a higher priority. These are all the possible outcomes and none of them make a compelling case for investing in LIDAR.
a vision only approach _may_ be possible at some time, but only with a strong computational model of the human brain and thought process.
also, most people drive poorly— i wouldn’t say vision is the be-all-end-all of autonomous driving. it’s also clear that waymo and cruise have taken a full sensor based approach and are successful, whereas tesla is not.
I broadly agree with your second point, about vision-only presenting big computational challenges. I think you do get some easy wins that bring down the challenge a bit - e.g. you don’t need to model human brains, you just need to model whatever the brain is doing when it’s driving; also the fact that we can teach people to drive without understanding what their brain is doing is a reassurance that we can teach a neural network to drive without understanding what it is doing either, so it frees us from (some) of the modeling of thought processes as well. But it is still a big computational challenge. I heard that Tesla has a server farm with thousands of Nvidia A100s, if true, that could make a dent in the problem for sure.
And yeah, I also wouldn’t say vision is the be-all and end-all when it comes to driving. (It’s a pity that we can’t easily integrate LiDAR, radar, and other sensors into the human brain so we could use them like we do sight and sound in order to drive better.)
My point is more that roads come in all shapes and types and sizes, but one consistent thing about them is that they’re all designed so that humans can use vision to drive on them. Like, you don’t know if future roads/signs/cars will be built in ways that are hard to read with LiDAR, but you can be pretty confident they won’t be built to be hard to see. Road builders, car makers - everyone else involved in the driving industry is designing for vision. It’s implicit, and it’s aimed at human vision, but it’s one of the few universal constraints on driving.
That’s what I mean when I say it’s a standards-based argument, that vision is sort of a “universal interface” for roads. Another “universal interface” for roads might be wheels (with traction), or more specifically tires. You don’t need to have rubber tires, or even wheels at all, to drive on roads - but if you do have tires, you can pretty confident that you can drive on pretty much any road you come across.
Quick disclaimer that this doesn't reflect the views of my employer, nor does any of what I'm saying about self-driving software apply specifically to our system. Rather I am making broad generalizations about robotics systems in general, and about Tesla's system in particular based on their own Autonomy Day presentations.
When you drive on the road as a human, you rely a lot more on intuition and feel than exact measurements. This is exactly the opposite of how a self-driving car works. Modern robotics systems work by detecting every relevant actor in the scene (vehicles, cyclists, pedestrians etc.), measuring their exact size and velocity, predicting their future trajectories, and then making a centimeter level plan of where to move. And they do all of this 10s of times per second. It's this precision that we rely on when we make claims about how AVs are safer drivers than humans. To improve performance in a system like this, you need better more accurate measurements, better predictions and better plans. Every centimeter of accuracy is important.
By contrast, when you drive as a human it really is as simple as "images in, steering angle out". You just eyeball (pun intended) the rest. At no point in time can you look at the car in the lane next to you and tell its exact dimensions or velocity.
Now perhaps with millions of Nvidia A100s we could try to get to a system that's just "images in, steering angle out" but so far that has proven to be a pipe dream. The best research in the area doesn't even begin to approach the performance that we're able to get with our more classical robotics stack described above, and even Tesla isn't trying to end-to-end learn it all.
That isn't to say it's impossible (obviously, humans do it) but I think one could make a strong argument that "images in, steering angle out" is like epsilon close to just solving the problem of AGI, and perhaps even a million A100s wouldn't cut it ;)
The best human drivers do this not at centimeter, but at the millimeter level. Look as downhill (motor)bike racing, Formula 1, WRC, etc..., These drivers can execute millimeter level accuracy maneuveurs that are planned well in advance at over 100km/h.
Basically humans are really really good at guesstimating with great accuracy (but poor reproducibility) and since we don't use basic measurements in the first place, having better measurement accuracy wouldn't really help us be better drivers on average (it does help for certain scenarios like parking though, where knowing the # of inches remaining to an obstacle can be very useful).
But for everyday driving at speed, we wouldn't even be able to process measurements in real time even if someone was providing them to us. AVs are different and that's basically the gist of what I was trying to say. Because they actually do use, rely on, and process measurements in real time, improving their measurement accuracy (ie. switching from camera based approximate depth, to cm level accurate depth from a LiDAR) can have a meaningful impact on the final performance of the system.
> humans do driving with ~only vision -> roads are therefore universally designed and built to be driven via by vision -> computers should do driving with only vision
What is 'should', is it a moral imperative? Is it a social obligation? Who made this argument, a catholic priest?
Where is consideration of this argument from an engineering perspectove - analysis of advantages disadvantages, where consideration of cost benefit? Where is assesment that, for example, 50% of human crashes are due to poor visibility or spatial awareness and comparison of how well computer handles them?
If I posted this vacuous, unsupported argument here, I would be laughed at, and rightly so.
But if Elon announces something, there is always 10% of the population willing to defend it, no matter how dumb it is.
Karpathy is one of the world's top self driving engineers. This isn't a vacuous argument. People are driving with just vision every single day. The part we're missing is the ChatGPT moment on the computational side.
From what I've heard firsthand Autopilot still steadily improves, irrespective of what people say about their favourite sensing modalities...
You can tell apart grass and green carpet with a simple formula. You can coint trees without machine learning. Yoi can detect which plants are whilting, land that is wet from land that is dry. All of that is easy with the right sensors - becauae they have more data than an RGB camera can produce.
I know people that work with mutispectral imagery, they can tell you that pixel N45 has a spesific substance - concrete, steel or wood - jusy from spectra alone. Thye dont need to know what pixels around it are showing, or classify objects.
It's not like Waymo dropped a LiDAR onto the roofs of their vehicles and started driving unsupervised in traffic the next day. Nor Cruise, nor Uber. The sensing is just a small part of the whole system.
This is one argument for vision alone. It’s easier for humans to teach the deep neural network what to do if they both see and label the same thing.
It’s harder to build labeling systems that work on representations that humans don’t understand like point clouds or noisy depth maps.
That isn’t to say that other sensors including radar, gps, LiDAR, other spectrum, etc don’t help.
But you have to develop more complex labeling methods or move away from supervised learning.
https://dataloop.ai/platform/lidar/
A good supervised learning process requires teaching humans to label consistently.
Imagine trying to write down precise instructions to train hundreds or thousands of humans to label many different types of objects using a tool like the above. Now hire, train, and manage those humans.
Compare that to having the humans draw rectangles around 2d color pictures of cars.
Also note that such tools need to be built and improved.
Is this maliciously specious or am I missing something? I drive using vision plus decades of life experience and all the tacit knowledge, judgement, and reasoning ability that comes from that. We have not reproduced any of that with math, and getting/stalling 90% of the way there with mimicry is not good enough.
If everyone could take some deep breathes and press pause on their emotional response to Elon Musk (and not assume everyone who happens to agree with him has a Musk tattoo) then they would fine plenty of rational arguments from an engineering perspective.
On top of that, you have theory of mind. For example, you have 4 cars next to you, all of them with opaque windows that do not let you see the driver:
A) a loud sports car with a bunch of modifications, decals and racing related stuff
B) a grandma car with cat related stickers
C) an unmaintained car with collision damage, and loud music coming from it
D) a family station wagon with a baby on board sticker and other family related stuff
Your mind will process what it sees and quickly assign each one of those cars a different personality. A and C will likely be perceived as riskier cars, B and D will be likely perceived as safer cars. You will avoid A and C and remain unconcerned about B and D.
The problem with the self-driving cars right now is that they only perceive the road as bodies that move.
I just imagined myself driving without sound. That seems crazy to me. I need to hear cars, kids playing, etc.
And you're right that we subconsciously assign risk values to each car. A heavily modified BMW with decals? Could be an irresponsible young male adult trying to show off on the road. I should probably be prepared to brake or let him go first.
AI will probably eventually very good at picking up these behavior tendencies. Or at least better than the people who aren't driving all day.
I'd rather have a computer keep track of everybody just the same but with millisecond reaction to all changes. Something that I can't do lacking eyes all around and processing power.
* Humans can drive with vision alone
* A sufficiently advanced compute system can drive with cameras alone
* Telsa's FSD computer cannot match human performance without additional sensors
The hard problems in autonomous driving are not related to sensing, but deciding what to do in weird or complex situations.
See this video for an example of a typical problem in recent FSD (and you can see from the screen that it's not related to sensing / detection): https://youtu.be/eY3z1kgX5hY?t=74
I work for Google and I like what Waymo has accomplished (disclaimer: what I work on is nowhere near Waymo). Tesla is making a different bet with different engineering resources. And why would Google give up their secret sauce to Tesla?
It's a hard problem to solve, but that doesn't mean it's a bad idea. I think most people would agree that human beings are better off with the overlapping set of sensors that are available to us compared to the alternative.
The thing is, Elon has lots of fans.
That said, there is no point making a self driving rig if it’s going to only be as good as the best humans are. For adoption, it must be provably better in any situation imaginable: moving obstacles, weather, dust, dark drunk humans in the night, emergency vehicles, no lanes drawn on the road, read all road signs correctly (say my Yaris gives me mistaken readings where maximum mass is confused with speed, it doesn’t know what “built-up” area means with regard to speed limits, it sometimes reads a sign that belongs to an adjacent road). For it all to work, you need more input than vision. And redundancy. Lots of redundancy.
Not the strongest of arguments.
“since humans move around on foot, that’s how we should design machines that help us move stuff around”
“Since humans do long-distance communication by shouting, hand or smoke signals, that’s how we should do it in transatlantic communication”
“since birds can fly using wings, that’s how we should do it in machines that fly”
Given what is public now, I'd speculate that perhaps they were working on replacing radar all this time. Then they used vision as an excuse to dump the existing radar early when there was a parts shortage.
I see Musk acting a lot like Jobs in certain ways. They were both very cagey about the future direction of their products. Although Musk didn't exactly backtrack on radar, he wasn't transparent about Tesla's plans either. You don't telegraph your moves to your competitors. Similarly, I'd be very surprised if Tesla wasn't keeping an eye out for lidar crossing a specific cost/function threshold. They're not saying that aloud, though.
Tesla has been working on building a high res radar since 2018 and have yet to officially announce anything. Tesla dropped radar in new vehicles in mid-2021.
That he later may have changed his tune is probably true, as reality does eventually catch up even with someone like him.
You listen to the road condition.
You sense the road bumping.
You feel the acceleration.
Your eye have better dynamic range.
The main argument after the collision? "I haven't seen them!".
Ultimately the market will only ask two things: Does it work? And, how much does it cost?
No-one cares that "Ah but ours only uses vision".
And it's a good bet. There's tons more to self driving than perceiving the world (lidar does not help a driver what to do in a novel and ambiguous situation, it's not a perception problem) and Tesla's vision is quite good based on all the FSD videos on YouTube.
Reducing that to "vision" doesn't even make superficial sense.
A model which can use predictive behaviour for the objects that the visual part detects seems orders of magnitude better than one that just does visual detection from scratch. Seems like a huge wasted opportunity to have to model the world starting from zero for every frame they receive from the cameras.
Objects that pop-in and out of the field of vision due to occlusion or other reasons seem to trip Teslas (in at least some of the reported incidents), but even like that it's hard to believe that they didn't implement such an obvious improvement.
You’ll need to solve vision anyway. Because you need to know what the object is. Is it a trash can or is it a dog? Will it move or stay?
If you had LiDAR, you’d still need sensor fusion with a camera to answer those questions, introducing more problems.
That’s why Elon says that any company that relies on LiDAR is doomed. LiDAR isn’t the gold standard - it’s the low hanging fruit.
Of course. The real argument is "LIDAR is expensive in comparison and after scamming people for almost a decade, we have to be careful what kind of money we ask for". LIDAR was never considered an overkill by Elon.
What is the basis for this claim? Have you seen the kind of data other sensors provide?
Radar gives you exact distance and velocity of a vehicle thats hundreds of meters away, through fog, in the dark.
Cameras can't even give you distance for objects that are too far away
Humans also use their sense of motion from the car sliding, rocking, tilting, jerking, etc.
Then humans integrate all such input, combine that with what they know about how cars work, traffic, people, the road, diagnose what has happened, apply years of prudent judgment, and then decide what to do.
E.g., maybe they have an ice chest with 20 pounds of ice which has melted and now, due to the motion of the car, has tilted, spilled, and is about to get the dog soaked with ice water. Good luck with the self-driving with a good response to such a scenario.
But that wouldn't be a problem if Tesla didn't advertise their cars as containing all the necessary hardware for self driving. If Tesla admitted that cameras were insufficient for self-driving, they would open themselves up to legal liability.
They got all the hype and PR for the AI angle without the money pit that comes with a real self driving project.
Even if they eventually get cannibalized by actual self driving cars then they still made billions and billions in the process.
Opinion: a lot of people in this space thought “no one wants to get in a car with a radar tower on top, can’t we make it just look like a car?”
And decisions proceeded from there.
Which is insipid because humans do not use just vision when driving. We use hearing, touch, and proprioception extensively when driving.
If they can finally make it work well one day, that comment will be the one looking dumb in the end.
just saying that one should be careful about making this kind of assumptions...
> if given additional senses, wouldn’t humans use them for safer driving?
It's all a question of costs in the end. It would be safer to fly with 10 pilots in one airplane, but the economics make it work for 2-3 at most.
Sounds great in practice but isn’t realistic in the slightest
And that's also why a "self driving" car isn't realistic.
I think the proper term for what we have now should, at most, be something more akin to "Assisted Driving Features" because right now it's far to blurry.
Thats what road are already. They are costly and they are mostly standard through out the world.
https://electrek.co/2019/11/07/tesla-autopilot-handle-constr...
There is no other day to day activity where this level of risk is considered acceptable.
More people have been killed by cars than I have.
Whataboutism but puts those numbers in perspective.
Guns… most of those are suicides, and that stat is uniquely American in terms of developed countries.
Opioids… also almost entirely self-inflicted (not willingly, but getting flattened by a bus is different than getting accidentally hooked)
Car stats also don’t count the incredible number of people who have lifelong or major injuries due to cars, which I would imagine is much higher. I feel pretty comfortable saying that a majority of people I know have been injured by cars, something that isn’t true for opioids or guns.
That seemed unbelievable to me, so I had to do some checking. The CDC[0] put 48k suicides in 2021, and attributed 55% to guns. Leaving us with 26.4k suicide gun deaths. While still a large number, there are still a significant portion of GP's 48k gun deaths which were not self inflected.
[0] https://www.cdc.gov/suicide/suicide-data-statistics.html
Anybody who says humans are bad drivers is almost certainly underestimating the difficulty of replacing humans by a factor of 1000x.
I mean, you wouldn’t say humans are good at tic-tac-toe, and bad at chess, right? Chess is just a much harder game.
[1]: https://www.iihs.org/topics/fatality-statistics/detail/state... [2]: https://en.wikipedia.org/wiki/Transportation_safety_in_the_U...
Compared to sharing roads going opposite directions at high speeds inches away from each other, it is no contest that humans driving is the much more impressive number.
And even GA pilots are probably in much better physical shape than the general public that drives cars.
That's actually not a very big number. 5000 years of regular driving is about the lifetime driving for 100-150 people. Which means one of them will have a fatal accident within their lifetime.
Given that, perceiving the environment with radar, lidar, visible light, infrared, and so on is equivalent to human vision.
As far as I'm aware, Tesla uses more than just visible light sensors. Am I wrong in my understanding?
You have input, taken by sensors, converted into usable form by a processor. There is no fundamental difference between visible light and radio waves, per se.
When paired with a general intelligence evolved over a couple million years, and visual sensors that have much more dynamic range than commercially available sensors yeah.
The problem is without those 2 things Teslas crash into fire trucks.
And different bands of EM have different properties so eyes aren’t equivalent to radar. Otherwise we would be able to see around corners.
And if humans had more sensory data we would definitely be integrating it into our driving. Otherwise ADAS tech wouldn’t be so commonplace in 2023.
Though, it seems Tesla reincorporated radar from their post '21 models on, so the premise of this sub-thread is at best outdated and at worst a half-truth. Oh well.