Tesla is not a good piece of evidence. They registered a grand total of 12.2 autonomous miles in 2019. Their "Autopilot" is a particularly fancy driver assist system; if you take their marketing at face value and treat it like an autonomous driving system you are putting yourself and everyone on the road at risk.

That's fair, I've just taken the marketing at face value.

Though I ended the answer at the end asking whether Lidar adds incremental or exponential value? Do you think it adds exponential value ?

I'm not an autonomous car engineer so don't understand the nuances but from whatever basic information I've read it doesn't seem like Lidar's add exponential value.

edit: Just to add, 5 million Waymo miles have been driven with a driver that controls the car and Waymo has had an accident too - https://www.wired.com/story/waymo-crash-self-driving-google-...

Also Waymo has way lesser cars on road than Tesla

Exponential. It gives range and shape data, which a pure-optical system needs to infer from a 2D image. This kind of image processing is still an open problem in ML.

The usual metric for self-driving car success is "disengagements per mile", ie how frequently a driver needs to intervene to avoid a crash. From my anecdotal readings of Tesla Autopilot reviews, it's on the order of 0.1 per mile. For Waymo and Cruise, it's on the order of 0.01 per THOUSAND miles. That's a very different definition of "driver" than the one that Tesla Autopilot requires.

I don't know the total number of miles on all Teslas on Autopilot, but it has had much more than one accident.

EDIT: and that Waymo crash was not a self-driving error; it was T-boned by a human-driven car running a red light.

Fair, depth perception from 2D isn’t there yet through ML, but mixed with radar can it be effective enough.

The reason I assumed it works is that lidar on the article above seems more like a redundancy. Because their camera system have the short range covered and radar has the long range covered. Lidar seems to augment over it.

Though the order of disengagement is a great stat, that definitely shows how much better waymo is compared to Tesla

> but mixed with radar can it be effective enough.

The usual solution is actually lidar + optical; lidar gives much better spatial resolution than radar, which is why it's been the standard going back to the DARPA challenge. You really want to have good spatial resolution in order to distinguish e.g. bikers and tail-lights and road signs for your optical systems, which radar typically isn't good enough for; that's the point of that qualifier in "imaging radar". Still probably worse performance (i.e. time and spatial resolution) than lidar, but better range and weather resistance.

(The previous generation of Waymo cars already had one lidar on top; the radar and the close-range lidars are the new additions.)

Their AutoPilot has driven billions of miles. Yes, the driver must still be paying attention and ready to take over. That doesn’t mean the system wasn’t driving.

Miles per disengagement I’m sure is not too high. That would be a good metric to have. But total miles is still ~2 billion.

> He's been a long time anti lidar proponent because of the costs involved and the aesthetics.

I can't help thinking that, whatever the merits of Lidar, Musk is boxed in, because Tesla has sold hundreds (tens?) of thousands of "self driving packages" for cars not equipped with Lidar, so changing course would not just mean raising prices on new cars, but retrofitting large numbers of existing cars at a ruinous cost.

That’s a fair point. He does have a bias to sell that story.

> Elon Musk's bet is that self-driving cars can just use just cameras, basic radar and ultrasonic sensors with enough compute resources and the right ML algorithms to perform better than a human.

I'm not sure that unsubstantiated claims from Elon Musk are actual evidence that lidar isn't necessary.

It's substantiated by the fact that humans don't have radar and ultrasonics, just two cameras on a swivel and a lot of signal processing, and they succeed at operating a car to five-nines reliability measured in miles traversed. So Musk's bet isn't completely bonkers; he knows of at least one reference system that does the task with fewer sensors than even shipped with the Tesla.

... but we do want the SDC to do better, and there are failure modes that human perception is also vulnerable to generally. In addition to closing the gap faster on solving the problem without a copy of the human perception wetware, the LIDAR signal might also improve on those perception error states and be worth keeping in the design even if it could be done with cameras alone (or camera + radar + ultrasonic).

I mean, sure, humans don't have radar or ultrasonics.

However, computers don't have human brains, and AI doesn't provide _anything like them_.

Defininitely agree, and I think that's the devil hiding in the details about Musk's bet that is worth surfacing: he's making the bet "We can just build a computer as good at this complex highly-variable task as a human being," and it's a bet people have been making and losing for decades.

Some day, someone will make that bet and be right. I haven't put my money on this team and this project. ;)

> the Tesla stack could be better than Lidar

From the systems I've worked with it's usually AND and not OR, you use both a Lidar and a Radar. The Radar images I've seen were quite lousy and are not 100% interference prone.

The problem is Tesla autopilot only works on highways and has been implicated in a number of crashes. Waymo seems to be taking the much more cautious approach of using every advantage they can get. Perhaps one day there will be self driving cars without lidar. But for now I think Waymo's results speak for themselves.

A few people died following that bet though

I don't have a Tesla nor am I a fanboy. Just talking about the tech.

This is biased information as there are way more Tesla's out there compared to Waymo's.

Waymo has had accidents too https://www.wired.com/story/waymo-crash-self-driving-google-...

Your evidence is a waymo car getting t-boned at an intersection?

By a car running a red light, no less.

I think it’s absolutely fair to expect autonomous vehicles to have awareness of a probable side collision in an intersection and be able to speed up or slow down to avoid it.

I often see oncoming cars rushing to make a left turn past when their arrow has turned yellow and red, and so I know not to enter an intersection even though my light has turned green.

Autonomous systems in theory should be better than humans at this because they can track all surrounding objects and trajectories, not just ones they are looking at with one set of eyes.

I think the accident rate is kind of a meaningless stats. You can have a low accident rate by carefully controlling the conditions under which you test. Not many accidents means they aren’t pushing the envelope. That’s probably a good thing on public roads. It’s also why the system is not available for general public use except under extremely controlled routes and close (remote) supervision.

I think it’s great we have (at least) two mega-companies in a race trying different approaches to reach a solution. There are good points for and against both approaches. This is what makes life interesting, you can’t just run the numbers to predict the future.

Thing is, Tesla is not one of the mega-corporations in the running; it's Waymo (Google), Cruise (GM), and possibly Apple.

Linking to an article about a waymo car being hit by a car in a side collision seems pretty disingenuous when comparing to the Tesla accidents that people usually talk about