I've been a Electrek reader for almost a decade. It's interesting to see its editor Fred Lambert from super pro-Telsa/Musk when fighting EV vs. ICE cars to anti-Telsa/Musk when Musk got into politics.
Of course Musk knew multi-modality would win true Level 4 autonomous driving. It was a calculated tradeoff to work on vision first when LiDAR (components cost 10s of thousands and unreliable for continuous functioning) and Radar (components cost thousands) when Telsa was battling production hell and has real threat of not making it.
Millions of Tesla on the road and 100s of thousands supercharging stations later, LiDAR becomes more reliable and affordable (just like how Tesla made the lithium batteries affordable).
Could Tesla re-incorporate LiDAR + Radar into their sensing stack in the future. I think so! After all, just a few short years ago, Telsa threw away of their 300k+ lines of C++ initial AI software stack based of MobileEye OEM in opting in their own Deep Learning based neural network model. Now, they might still there are still room for camera/vision only assisted driving technology.
Waymo's modified Jaguar model costs $150k-$200k apiece fully loaded with 3 modalities. Tesla Cybercab production cost is below $30k. They are on DIFFERENT segment. Comparing them is like comparing Toyota Corolla vs. Feferrari for their engine output, absurd!
So, this article feels like another emotional biased hit piece of Lambert jabbing at Musk which is daily occurrence now at Electrek.
I thought the pitch for just-cameras was that the hardware was cheaper and that it's what humans are "using", evidence that it should be sufficient. Just-cameras was to take more engineering to build upnfront but pay off in lower costs in the end. That argument disagrees with the graph that's presented.
Sure, cameras (eyes) are mostly all that humans are using, but two points:
1) the vehicles aren't quite matched with the same experience and intelligence (right now) as exists behind a human's two "cameras"
2) we hold self-driving robots to a much higher standard. meatbags are getting smushed in large numbers daily by other humans, but a single robot smushing a human is headline news for days. giving the robot vastly more information about the world around it, in much higher detail will eventually allow it to drive much better than us.
[obviously we should hold them to higher standards, we should create something much better at driving than the best humans]
The argument made more sense 5+ years ago, but the hardware costs of sensors such as LIDAR has plummeted.
In addition, a certain CEO of a certain car company has made very aggressive sales pitches about how LIDAR isn't necessary and even going so far as to sell unfinished self driving solutions as being completely capable of doing so.
So hypothetically, if that car company were to adopt LIDAR, they would have been selling their solution under false claims in a sales capacity.
$60,000 for car with sensors? I'm delighted to hear Waymo may be anticipating such low price points:
"We are hearing that Waymo is close to having its entire package (car + Waymo sensor suite and driver) at around $60,000"
Personal experience, but my Tesla Model 3 drives most trips from start to finish. If I have to intervene, it's usually because other drivers aren't letting it into a lane and I have to get aggressive. Friends I know in Dallas and Austin (simpler, friendlier streets than where I live) say they don't drive at all anymore. Maybe it's not good enough for a robotaxi service yet, but the rate of progress since my first Tesla in 2022 has been crazy to watch, especially in the last year.
Conversely, I've tried Waymo in Austin and SF many times, and while I enjoyed the experience overall (much better than Uber) it seemed to make a number of mistakes my Tesla wouldn't. In Austin they've struggled to pull up to the right pickup spot and taken very odd backroads (apparently b/c they struggle with certain intersections), and in SF a remote driver had to take over driving because my Waymo (along with another one behind me) got stuck behind a car that was double parked.
Because Waymo is largely unsupervised, they take a much more conservative route than Tesla does. Their route planner includes avoiding high-incident rate stretches of road.
If there is a stretch of surface road with a complex intersection and aggressive drivers, you are there to step in. The Waymo Driver instead will try to avoid that area.
Also, Tesla's hardware is not nearly complex or powerful enough to approach the low level of intervention or incident rate that Waymo has - but HW5 will be a massive step forward for them.
That's going to be the make or break for me, personally. If Tesla can't make their solution work well on HW5, then they have serious structural issues in their program.
Tried FSD once. It was very confused about a traffic circle, cruised up to it & slammed on the brakes. Got rear ended (at low speed).
The incomplete, miscategorizing and glitching display of other vehicles and obstacles does not give me confidence that the car is able to correctly identify whatâs around it, let alone drive accordingly.
Even the lane departure warnings are 90% false positives (but Iâd rather be warned than not).
Just driving normally is much less stressful and more fun than supervising the carâs attempt at driving like a teenager.
Lidar will give you XYZ (z = distance) on a single datapoint, cameras give you XY and you need to calculate the Z from multiple cameras.
Lidar is ugly and expensive, but requires way fewer cycles to calculate distances. And it works through fog and even some obstacles, nor does it care about glare or get "scared" of shadows.
If we had infinite compute in the car, cameras would be the obvious solution ...but we don't. You can get "Pretty good" with cameras, but still people find specific spots where the car is 100% sure a shadow under a bridge is a car or something stupid like that.
"depth estimation" precision matters! and it's still prone to optical illusions and other issues (many solutions struggle with road shadows, for example. sound familiar?)
I think the natural solution is a 360 lidar as a source of truth, followed by optical for everything else
> âHumans of course can drive with just eyes, so thereâs that proof of existence,â he said. âIf the goal were to just approximately match human performance or to build an assist product, thatâs a very reasonable way to go.â
It feels like there's a lot of assumptions baked in here. For example, do humans get in accidents because eyes are insufficient driving sensors? Or because human drivers get tired, distracted, make mistakes, etc.
Also, you can put 10 cameras on a car looking in all directions at the same time, which feels materially different from a human that only has 2 eyes which can only look in a single direction at a time.
It's possible that massively superhuman driving performance can't be achieved with just cameras, but I'm not seeing a strong case for that being made here.
Humans also have prior world domain knowledge. A human driver seeing a guy running across the road behind an obstacle can infer that the human will probably pop out on the other side (and prepare accordingly). A human can see the silhouette of an object with 1 eye and still infer that it has depth because they know what objects are, which is why one-eyed people can drive legally everywhere in the US. This inference extends to everything, not just shapes but behaviors of anything in the road, animate and inanimate objects.
Competitor explains why competition's product falls short - film at 11. I'd say the proof is in the pudding, which system shows the best results under different circumstances. I suspect the end result will be that a combination of cameras and some scanning apparatus - lidar, radar, sonar - gives the best results and that self-driving systems will converge on that combination.
We already have those results. Itâs why Waymo is doing millions of paid rides per month while Tesla is LARPing a robotaxi service thatâs basically doing zero fully autonomous rides, as far as anyone can tell.
If Teslas could self drive you could sit in the back seat, or sleep, or send the car somewhere without being in it. Elon really wants them to, but Tesla's do not self drive.
"FSD (Supervised)" is a marketing name... which they updated with the parenthetical almost certainly because of brewing legal issues with false advertising. It does not self-drive.
> FSD (Supervised) is an advanced driver assistance system that is intended to be used only with a fully attentive driver. It does not turn a Tesla into a fully autonomous vehicle.
You can't buy a self-driving Tesla today. Even Tesla tells you that in the fine print. Its self-driving (supervised). If it was actually self driving, they wouldn't be saying (supervised).
Also, contrary to your statement, the article directly addresses the meat if the question:
> The disagreement is whether âgood enough to help a human driveâ ever becomes âgood enough to remove the human,â and his answer is no, because the sensing tops out before you get the last few nines.
> Now, Tesla would point to its active Robotaxi service as an example of âremoving the humanâ, but Dolgov also said that camera-only is also good for a demo, and thatâs basically what Teslaâs Robotaxi service is right now.
LIDAR units are nowhere near that expensive.
Even ten years ago, the Velodyne top of car units only cost about $80,000.
The short range ones, found at vehicle corners and on the rear, are now around $200 - $1500.
The long range car-top unit is still expensive, around $10,000, and that's dropping. The whole sensor suite on a Waymo is probably under US$20,000 right now. If that.
The future direction for automotive seems to be more car-top sensors with narrower fields of view that add up to a full circle. Only the one that looks ahead needs 300m range.
Article has a paragraph about how lidar is rapidly getting cheaper, so the camera comparison is only temporary
Dolgov also pushed back on the one knock that camera-only fans always reach for: cost. Waymo is on its sixth generation of hardware, and he said each generation has drastically cut the price. Betting against sensors like lidar on todayâs prices, he warned, means betting on âa number that has a fairly short shelf life.â
Thats the million (billion? trillion?) dollar question. Will it get cheap enough? Will it get cheap enough to put on 100 million+ vehicles and be competitive with cameras? I honestly don't know the answer, but I haven't seen strong evidence to point to yes.
If 2x Mk 1 eyeballs are good enough then I figure cameras can get there too. Or are we going to outlaw that as well because of competitive incentives of Waymo?
Do you have any conception of how massively, incomprehensibly, extremely superior our sensory system is to any kind of camera-based computer vision we can make?
In terms of dynamic range and color space? Yes absolutely. But for driving you don't really need a huge color space and for dynamic range you can just use separate cameras for daytime and nighttime.
Even the average human ends up with about 1 fatality every 100 million miles and 1 serious injury every 10 million miles. The typical person will drive somewhere in the six figures of miles in their lifetime.
I wish I were as rich as Elon but alas I'm just an ordinary person who appreciates more than one company competing to deploy autonomous driving technology. Appreciate the vitriol though, it tells me a lot about you as a person.
Excuse me did you just call me a highly corrosive acid made from sulfur dioxide? Reported.
edit: I also want to point out that the fanboys conflate documented evidence in wikipedia of things EM has said with vitriol. It's like when people get banned on social media for hate speech for quoting something the POTUS said.
Nope, you need a regulatory approval, insurance etc. Self driving cars need to be 10x the average driver. So the trillion dollar question is when Lidar will meet all requirements and when camera-only.
> Self driving cars need to be 10x the average driver.
Why? So long as they're insured and their owners can be held criminally liable for injuries just as a human driver would be, why does the bar have to be higher?
Because driving risk is far from evenly distributed. If a self-driving car drives like an average human driver, for responsible drivers, this would mean incurring more risk by getting into one.
A huge portion of the risk of human drivers is due to confounding human factors like negligence, distraction, medical issues, fatigue, etc. Responsible drivers can take most of these factors into their own hands -- not driving while sleepy, not driving drunk, not using their cell phone. These people don't want a vehicle
A better comparison would be comparing the capability of a self-driving car to the skill of a human driver driving under ideal circumstances of health/responsibility/etc.
Personally I would rather vote to ban them if they aren't safe enough. If car makers want to cheap out at the expense of public safety they should go to prison for the people they kill.
> I wonder if you could prevent glare by placing an LCD-like device in front of the lens dynamically blocking out the sun.
Elon has already lied, on an investor call, about how such things are not necessary - he referenced how "Tesla cameras can count photons", as a reason why they were not affected by fog, rain, or snow.
Except, no they can't, and they never will be able to. Not the cameras in any Tesla now (and even then). It's a completely different type of camera (and it would do effectively nothing useful from a visualization perspective, let alone functional camera for human viewing). And even if they changed the camera, or added some, well, you can't count photos if you're not in an enclosed space (you know, like the open road).
This is where Elon gets really dangerous, in my mind, he knows enough to be dangerous, he knows what to say that convinces the layperson, or investor, passes the initial sniff test only to dramatically fall over when you investigate.
Also worth watching the source presentation which is really interesting and informative beyond the Waymo specifics: https://www.youtube.com/watch?v=Gp4zrV3-6N8
I've been a Electrek reader for almost a decade. It's interesting to see its editor Fred Lambert from super pro-Telsa/Musk when fighting EV vs. ICE cars to anti-Telsa/Musk when Musk got into politics.
Of course Musk knew multi-modality would win true Level 4 autonomous driving. It was a calculated tradeoff to work on vision first when LiDAR (components cost 10s of thousands and unreliable for continuous functioning) and Radar (components cost thousands) when Telsa was battling production hell and has real threat of not making it.
Millions of Tesla on the road and 100s of thousands supercharging stations later, LiDAR becomes more reliable and affordable (just like how Tesla made the lithium batteries affordable).
Could Tesla re-incorporate LiDAR + Radar into their sensing stack in the future. I think so! After all, just a few short years ago, Telsa threw away of their 300k+ lines of C++ initial AI software stack based of MobileEye OEM in opting in their own Deep Learning based neural network model. Now, they might still there are still room for camera/vision only assisted driving technology.
Waymo's modified Jaguar model costs $150k-$200k apiece fully loaded with 3 modalities. Tesla Cybercab production cost is below $30k. They are on DIFFERENT segment. Comparing them is like comparing Toyota Corolla vs. Feferrari for their engine output, absurd!
So, this article feels like another emotional biased hit piece of Lambert jabbing at Musk which is daily occurrence now at Electrek.
The general approach to pioneering work like self-driving is:
1) Make it work
2) Make it right
3) Make it cheap
For no good reason, Elon tried to solve step 3 before the other two. This is extra strange since SpaceX has done much better at pioneering work.
Thatâs because SpaceX is Gwynne Shotwell.
Tesla did not make Lidar affordable. They don't even use lidar.
They also did not make lithium batteries affordable. Panasonic and CATL did that. Tesla was simply the first to exploit that bew affordability.
I thought the pitch for just-cameras was that the hardware was cheaper and that it's what humans are "using", evidence that it should be sufficient. Just-cameras was to take more engineering to build upnfront but pay off in lower costs in the end. That argument disagrees with the graph that's presented.
Sure, cameras (eyes) are mostly all that humans are using, but two points:
1) the vehicles aren't quite matched with the same experience and intelligence (right now) as exists behind a human's two "cameras"
2) we hold self-driving robots to a much higher standard. meatbags are getting smushed in large numbers daily by other humans, but a single robot smushing a human is headline news for days. giving the robot vastly more information about the world around it, in much higher detail will eventually allow it to drive much better than us.
[obviously we should hold them to higher standards, we should create something much better at driving than the best humans]
The argument made more sense 5+ years ago, but the hardware costs of sensors such as LIDAR has plummeted.
In addition, a certain CEO of a certain car company has made very aggressive sales pitches about how LIDAR isn't necessary and even going so far as to sell unfinished self driving solutions as being completely capable of doing so.
So hypothetically, if that car company were to adopt LIDAR, they would have been selling their solution under false claims in a sales capacity.
$60,000 for car with sensors? I'm delighted to hear Waymo may be anticipating such low price points: "We are hearing that Waymo is close to having its entire package (car + Waymo sensor suite and driver) at around $60,000"
The 100% tariffs on Chinese cars have been the biggest obstacle from not getting to that cost point sooner.
Personal experience, but my Tesla Model 3 drives most trips from start to finish. If I have to intervene, it's usually because other drivers aren't letting it into a lane and I have to get aggressive. Friends I know in Dallas and Austin (simpler, friendlier streets than where I live) say they don't drive at all anymore. Maybe it's not good enough for a robotaxi service yet, but the rate of progress since my first Tesla in 2022 has been crazy to watch, especially in the last year.
Conversely, I've tried Waymo in Austin and SF many times, and while I enjoyed the experience overall (much better than Uber) it seemed to make a number of mistakes my Tesla wouldn't. In Austin they've struggled to pull up to the right pickup spot and taken very odd backroads (apparently b/c they struggle with certain intersections), and in SF a remote driver had to take over driving because my Waymo (along with another one behind me) got stuck behind a car that was double parked.
Any actual Tesla drivers want to weigh in here?
Because Waymo is largely unsupervised, they take a much more conservative route than Tesla does. Their route planner includes avoiding high-incident rate stretches of road.
If there is a stretch of surface road with a complex intersection and aggressive drivers, you are there to step in. The Waymo Driver instead will try to avoid that area.
Also, Tesla's hardware is not nearly complex or powerful enough to approach the low level of intervention or incident rate that Waymo has - but HW5 will be a massive step forward for them.
That's going to be the make or break for me, personally. If Tesla can't make their solution work well on HW5, then they have serious structural issues in their program.
Tried FSD once. It was very confused about a traffic circle, cruised up to it & slammed on the brakes. Got rear ended (at low speed).
The incomplete, miscategorizing and glitching display of other vehicles and obstacles does not give me confidence that the car is able to correctly identify whatâs around it, let alone drive accordingly.
Even the lane departure warnings are 90% false positives (but Iâd rather be warned than not).
Just driving normally is much less stressful and more fun than supervising the carâs attempt at driving like a teenager.
Lidar will give you XYZ (z = distance) on a single datapoint, cameras give you XY and you need to calculate the Z from multiple cameras.
Lidar is ugly and expensive, but requires way fewer cycles to calculate distances. And it works through fog and even some obstacles, nor does it care about glare or get "scared" of shadows.
If we had infinite compute in the car, cameras would be the obvious solution ...but we don't. You can get "Pretty good" with cameras, but still people find specific spots where the car is 100% sure a shadow under a bridge is a car or something stupid like that.
> you need to calculate the Z from multiple cameras.
You can get 3D depth estimation from a single 2D image but I donât know how good it is for automotive.
https://huggingface.co/tasks/depth-estimation
"depth estimation" precision matters! and it's still prone to optical illusions and other issues (many solutions struggle with road shadows, for example. sound familiar?)
I think the natural solution is a 360 lidar as a source of truth, followed by optical for everything else
[dead]
i know this doesnt take away from the point of the article, but the whole thing is written by ai which just immediately makes me distrust it
> âHumans of course can drive with just eyes, so thereâs that proof of existence,â he said. âIf the goal were to just approximately match human performance or to build an assist product, thatâs a very reasonable way to go.â
It feels like there's a lot of assumptions baked in here. For example, do humans get in accidents because eyes are insufficient driving sensors? Or because human drivers get tired, distracted, make mistakes, etc.
Also, you can put 10 cameras on a car looking in all directions at the same time, which feels materially different from a human that only has 2 eyes which can only look in a single direction at a time.
It's possible that massively superhuman driving performance can't be achieved with just cameras, but I'm not seeing a strong case for that being made here.
Also humans can move their heads around which gives extra parralax information and thus better depth perception than two static cameras would imply.
Humans also have prior world domain knowledge. A human driver seeing a guy running across the road behind an obstacle can infer that the human will probably pop out on the other side (and prepare accordingly). A human can see the silhouette of an object with 1 eye and still infer that it has depth because they know what objects are, which is why one-eyed people can drive legally everywhere in the US. This inference extends to everything, not just shapes but behaviors of anything in the road, animate and inanimate objects.
You know...AIs these days, have that too. Not as good as humans yet, but it will surpass at some point.
https://www.reddit.com/r/TeslaFSD/comments/1u5eetx/hw4_fsd_a...
Competitor explains why competition's product falls short - film at 11. I'd say the proof is in the pudding, which system shows the best results under different circumstances. I suspect the end result will be that a combination of cameras and some scanning apparatus - lidar, radar, sonar - gives the best results and that self-driving systems will converge on that combination.
We already have those results. Itâs why Waymo is doing millions of paid rides per month while Tesla is LARPing a robotaxi service thatâs basically doing zero fully autonomous rides, as far as anyone can tell.
I can purchase a self-driving Tesla at a reasonable price, in-line with other cars of the same class.
I can't purchase a Waymo at any price.
You can't purchase a level 3 Tesla at any price, either.
To me, true self-driving starts at level 3. Otherwise, it's supervised.
And Tesla selling their product as "Full Self Driving (Supervised)" is like selling "Fully Cooked Meal (Frozen)". No! You call it a "frozen meal"!
If Teslas could self drive you could sit in the back seat, or sleep, or send the car somewhere without being in it. Elon really wants them to, but Tesla's do not self drive.
If Rivian was completely equal with Tesla at FSD, your tone would be completely different about Rivian. We understand.
Elon's an ass, but the world needs self driving in as many places, from as many providers, as soon as possible.
I wish Elon wasn't so stubborn about admitting he was wrong.
"FSD (Supervised)" is a marketing name... which they updated with the parenthetical almost certainly because of brewing legal issues with false advertising. It does not self-drive.
https://www.tesla.com/support/fsd#pay-attention
> FSD (Supervised) is an advanced driver assistance system that is intended to be used only with a fully attentive driver. It does not turn a Tesla into a fully autonomous vehicle.
"self-driving" in better than ideal conditions.
You can't buy a self-driving Tesla today. Even Tesla tells you that in the fine print. Its self-driving (supervised). If it was actually self driving, they wouldn't be saying (supervised).
My 2013 Prius does this too, if I let go of the wheel it goes basically straight until it needs me to take over and adjust its trajsctory
What does this have to do with anything at all?
Right. But are $200K worth of extra sensors actually worth it or are 10+ cameras already safe enough?
This article makes no attempt to answer the actual meat of the question.
Ultimately, people will vote with their wallet.
p.s. I wonder if you could prevent glare by placing an LCD-like device in front of the lens dynamically blocking out the sun.
Where did you get $200k worth of extra sensors?
Also, contrary to your statement, the article directly addresses the meat if the question:
> The disagreement is whether âgood enough to help a human driveâ ever becomes âgood enough to remove the human,â and his answer is no, because the sensing tops out before you get the last few nines.
> Now, Tesla would point to its active Robotaxi service as an example of âremoving the humanâ, but Dolgov also said that camera-only is also good for a demo, and thatâs basically what Teslaâs Robotaxi service is right now.
LIDAR units are nowhere near that expensive. Even ten years ago, the Velodyne top of car units only cost about $80,000.
The short range ones, found at vehicle corners and on the rear, are now around $200 - $1500. The long range car-top unit is still expensive, around $10,000, and that's dropping. The whole sensor suite on a Waymo is probably under US$20,000 right now. If that.
The future direction for automotive seems to be more car-top sensors with narrower fields of view that add up to a full circle. Only the one that looks ahead needs 300m range.
Current estimates put the Ojai sensor cost between $15k and $30k. My inclination is that there is confusion between BOM and constructed cost.
Article has a paragraph about how lidar is rapidly getting cheaper, so the camera comparison is only temporary
Dolgov also pushed back on the one knock that camera-only fans always reach for: cost. Waymo is on its sixth generation of hardware, and he said each generation has drastically cut the price. Betting against sensors like lidar on todayâs prices, he warned, means betting on âa number that has a fairly short shelf life.â
Thats the million (billion? trillion?) dollar question. Will it get cheap enough? Will it get cheap enough to put on 100 million+ vehicles and be competitive with cameras? I honestly don't know the answer, but I haven't seen strong evidence to point to yes.
> Will it get cheap enough?
An Ojai costs less than a mid tier luxury vehicle. Is that not cheap enough?
And the price is only coming down.
Itâs already there.
"Ultimately, people will vote with their wallet"
Seems like a bad way to legislate this, since everyone else on the roads pays the price for cut rate self driving
If your goal is to make roads safer, then making self driving more expensive and harder to afford will have the opposite effect.
If 2x Mk 1 eyeballs are good enough then I figure cameras can get there too. Or are we going to outlaw that as well because of competitive incentives of Waymo?
Do you have any conception of how massively, incomprehensibly, extremely superior our sensory system is to any kind of camera-based computer vision we can make?
In terms of dynamic range and color space? Yes absolutely. But for driving you don't really need a huge color space and for dynamic range you can just use separate cameras for daytime and nighttime.
Tesla fanboys aren't known for logic or rigorous thinking.
Well yeah, have you seen how badly some of you people drive?
Even the average human ends up with about 1 fatality every 100 million miles and 1 serious injury every 10 million miles. The typical person will drive somewhere in the six figures of miles in their lifetime.
Hi, Elon! Big fan of the Wiki page about your list of predictions for autonomous driving: https://en.wikipedia.org/wiki/List_of_predictions_for_autono...
I wish I were as rich as Elon but alas I'm just an ordinary person who appreciates more than one company competing to deploy autonomous driving technology. Appreciate the vitriol though, it tells me a lot about you as a person.
Excuse me did you just call me a highly corrosive acid made from sulfur dioxide? Reported.
edit: I also want to point out that the fanboys conflate documented evidence in wikipedia of things EM has said with vitriol. It's like when people get banned on social media for hate speech for quoting something the POTUS said.
> Ultimately, people will vote with their wallet.
Nope, you need a regulatory approval, insurance etc. Self driving cars need to be 10x the average driver. So the trillion dollar question is when Lidar will meet all requirements and when camera-only.
1) Both in 2028
2) lidar in 2030 and cameras in 2035
3) Gov will require lidar for full self driving
> Self driving cars need to be 10x the average driver.
Why? So long as they're insured and their owners can be held criminally liable for injuries just as a human driver would be, why does the bar have to be higher?
Because driving risk is far from evenly distributed. If a self-driving car drives like an average human driver, for responsible drivers, this would mean incurring more risk by getting into one.
A huge portion of the risk of human drivers is due to confounding human factors like negligence, distraction, medical issues, fatigue, etc. Responsible drivers can take most of these factors into their own hands -- not driving while sleepy, not driving drunk, not using their cell phone. These people don't want a vehicle
A better comparison would be comparing the capability of a self-driving car to the skill of a human driver driving under ideal circumstances of health/responsibility/etc.
1) Marketing and PR - people fear self driving cars
2) Politics - loss of jobs and urge to ban them - there needs to be a counterargument
3) Government does mandate a lot of safety features. Just insure it wont fly as this is number one risk for everybody.
Personally I would rather vote to ban them if they aren't safe enough. If car makers want to cheap out at the expense of public safety they should go to prison for the people they kill.
It's not car makers. It's car buyers. When a car buyer cannot afford self driving they'll just drive themselves.
The bar should be safer than a human and cheap, so more people can afford them.
Which is why we need strong regulation. People shouldnât be able to vote with their wallet when other peoples lives are at stake.
> But are $200K worth of extra sensors actually worth it
Of course not!
So, you may be surprised to find that Waymo's sensor package doesn't cost $200k. Whoops!
Youâre like 2-3 orders of magnitude off on your cost there.
> I wonder if you could prevent glare by placing an LCD-like device in front of the lens dynamically blocking out the sun.
Elon has already lied, on an investor call, about how such things are not necessary - he referenced how "Tesla cameras can count photons", as a reason why they were not affected by fog, rain, or snow.
Except, no they can't, and they never will be able to. Not the cameras in any Tesla now (and even then). It's a completely different type of camera (and it would do effectively nothing useful from a visualization perspective, let alone functional camera for human viewing). And even if they changed the camera, or added some, well, you can't count photos if you're not in an enclosed space (you know, like the open road).
This is where Elon gets really dangerous, in my mind, he knows enough to be dangerous, he knows what to say that convinces the layperson, or investor, passes the initial sniff test only to dramatically fall over when you investigate.