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Comment by infecto | Hacker News Reader

This an explanation from a layman on the auto side.

Tesla has focused on attempting to solve all cases using vision and generalize it as much as possible. The pro is you would be able to drop FSD capabilities anywhere in the US and it will work. The con is the tail of edge cases take significantly more effort then the first 80%.

Waymo instead of being generalized, works off of a detailed map for each region they drive in. They have a complete expectation of every detail on those roads and so then only need to account for the dynamic unknowns on the road. The pro is that they are getting to hands off driving sooner. The con is that anywhere its deployed needs detailed mapping and for that mapping to be kept up to date.

Time will tell which strategy pays off.

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> Waymo instead of being generalized, works off of a detailed map for each region they drive in. They have a complete expectation of every detail on those roads and so then only need to account for the dynamic unknowns on the road.

This isn't entirely true. Everything at Waymo is built to be generalizable. Engineers and execs at Waymo have said to multiple times, as recently as yesterday [1].

They are able to drive just fine without up-to-date maps as well. It's an assumption built in to the system. The cars are also self-mapping. Ultimately, maps are just another input to the general driving software. The same driving software is deployed across all their cities.

[1] https://www.youtube.com/watch?v=d6RndtrwJKE

Are they deployed into any cities where they are not actively mapping?

They test in many cities (Buffalo, Tahoe, Bellevue, NYC) . But they won't deploy to any cities which they haven't mapped because they consider it critical to safety.

> But they won't deploy to any cities which they haven't mapped

And therein lies the fundamental flaw with Waymo's approach...

It's not a flaw if that's what is required to make it work. So far only Waymo works at L4 autonomy, so they are vindicated.

As compared to what, Tesla's FSD that tries to crash the car every 20 miles or so?

So the answer is no and that's why I outline it as a potential con. They are unable to just drop deployment into a new city, they as a matter of history, map out the entire city and keep an active map of the driving territory. I have no idea who wins in this dog and pony show but I think its a valid potential con and a easy way to see some of the decision differences in companies.

Does Google Earth/Maps/StreetView not count as mapping? I was feeling certain that all that infrastructure and data was invested into Waymo. It would seem that Google had a huge advantage from running mapping/camera cars for years and years, before SDC were even a glimmer in their eyes.

The mapping that waymo uses is much more detailed than streetview, the biggest difference being that it includes lidar data. I wouldn't be surprised if they combined the two for some of their latest data updates, but the pre-existing streetview data is not obviously enough to give an advantage.

A map is really just a data cache, I've been surprised so many technical people see it as a flaw. It seems like an important feature to me!

A cache is exactly how I explain maps to people. They are saving precious compute cycles not computing the same static objects over and over again, by N number of vehicles.

A con does not have to be a flaw. But I would see it as a tradeoff. With all of these companies its hard to sometimes see beneath the curtain of what they promote.

Obtaining a detailed map doesn't seem difficult. This is the same company that created Street View. E.g. SF has ~1000 miles of streets [1], that would only take 50 hours of paying for manual driving to map all of SF at 20mph.

1. https://data.sfgov.org/City-Infrastructure/Miles-Of-Streets/...

Never said it was difficult but that their driving fleet relies on a lidar map of the region it serves. Its a definite trade-off so I would list it as a con but it does not mean one is better than the other.

Elon said a couple of days ago Tesla cars might never be able to self drive.

https://futurism.com/elon-musk-realizes-all-teslas-self-driv...

And probably because of this strategy, by the time their system is successfully deployed in several cities, the technology to make fully self driving has become much more accessible and they can relatively easily add that incrementally.

I don't see it as a significant dis-advantage for Waymo.

With modern drones and UAV, getting millimeter level details on infrastructure should be easy and cheap.

I would expect such maps for every corner of the world in next 5 to 10 years.

The other pro is cost: cameras are much, much cheaper than LiDAR. Tesla is making the bet that they can close the performance gap between cameras and LiDAR faster than the cost of LiDAR will come down.

I wonder if this will ever be a significant factor. How much can a LiDAR setup cost? 4k? Maybe 2k if built in-house at car manufacturer scale in the long term? Is that significant when buying a whole car?

if i am interested in reading more about this, can you point me to some resources?

Google "waymo dolgov" on YouTube, there's a recent lecture and a recent interview by Dmitri Dolgov. In the lecture, he talks about their architecture.

I’d advise you to ignore lay explanations of the space - outside of the industry most of the discourse about self driving cars is poisoned by Elon’s deceptive presentations and his followers who parrot what he says.

If you want a grounded explanation of how Tesla’s stack works, follow @greentheonly on twitter. He’s a Tesla reverse engineer who regularly posts about the software that’s actually running on the car.

If you want an explanation about how real AV companies stacks work, I’d read Sebastian Thrun’s robotics textbook - then imagine what’s outlined in that book but with ML plugged in to a ton of spaces throughout the stack. This is also similar to how Tesla’s stack works, btw - greens just good to follow because a lot of people refuse to believe Tesla isn’t running some kind of “LLM but for driving” fully end to end black box model.

Tesla won’t launch a robotaxi anytime soon because they can’t use remote support or HD maps - although I think they’ve been stepping up their mapping efforts. Even the demo at Universal studios a few weeks ago was HD mapped - per @greentheonlys twitter.

I worked in the space for years and have seen the internal of both a traditional robotaxi company’s stack and Tesla’s.

Unfortunately the industry like many others are poisoned on many ends. I would caution taking anyone's opinion too strongly including this one.

For reference, Sebastian Thrun led the Stanford team that won the Darpa (self driving car) Grand Challenge in 2005, and then joined Google to lead Waymo (then called the Google Self-Driving Car Project), among other accomplishments.

NOVA episode: https://www.youtube.com/watch?v=vCRrXQRvC_I

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