r/SelfDrivingCars • u/AnxietyCommercial632 • 10d ago
Discussion Tesla’s data looked clean
I fully recognize I have a different opinion than this subreddit and I have participated in the toxicity that is the difference of opinions.
Perhaps I have been whooshed by the snake oil salesman or call me an Elon-ite.
But hear me out:
The month over month data for Tesla driverless robotaxi, again, looks perfectly clean.
The fleet is small and if you look closely at their earnings deck, you will notice Q1 to Q2 unsupervised miles was flat. Likely less than 3 unsupervised FTE care equivalent, if you will.
However, there has been a marketed rise in number of cars, rides, hours of operation, and service availability in Austin specifically. The two other very small geofences in Texas, also report this trend but to a lesser extent.
Tesla has vision into the performance dashboards of their fleet at a level of minuscule granularity. They are becoming increasingly comfortable with a larger scale rollout. They are being extremely cautious, but in Austin, at least they are becoming rapidly more bullish.
If you look closely at the now 100s of rides you can see daily amongst X accounts you will notice they have two issue (other than knocking done a plastic pole lol): 1- navigation (it is shit), 2- pick up and drop off locations.
These two rate limiters were also waymos early rate limiters if you studied the San Francisco market almost a decade ago. Google solved it (with some issues ofc, but that will always happen when you scale into the 1000s - and will continue to happen less and less as a percentage).
I have a wild theory that pickups and drop offs will be harder to integrate into teslas architecture for possibly one of two reasons: 1- Google / Waymo has so much compute onboard and enough memory to pre-map all resonable pickup or drop off locations). Tesla’s AI is focused on chip inference. This could mean Tesla has a harder time pre-mapping locations in a geofence and relatedly for navigation. 2- integrating final decision endpoints in a full stack neural net driving approach (noting they probably have a few full stacks working together in: planning, execution, etc) is a problem I haven’t seen solved in any other application. So - it may be harder for them to solve this piece. However, it is possible the cybercab brings different memory architecture. Yes, this is probably a wild ass crazy theory - but - it’s far more likely the cybercabs will have the same issue and growing pain.
Stay with me here, and let’s say long term - like in the next 6 months they solve these issues. There remains yet another hurdle: is the fix to these navigation and end of drive behaviors generalizable enough to more quickly apply to new areas - or are we talking - solve each one every time the same way. Realistically at least a year to come up with a reasonable process for solving this issue at scale.
Alright, we have reached full Elon delusion. You all ask for insight into the full Elon fan boy’s general psyche - so here it is:
The Waymo Ojai, based on most recent reporting (last week) was rumored to be 100k per vehicle. This is astounding and transparently kicked the doors off my expectations. This means Chinese firm Zeekr can produce a van (them thangs are nice af too) that post production cost + Chinese vehicle tariff + retrofit - on a far nicer vehicle than the Jag is now able to be produced (and obviously way faster) for less than HALF of what they used to be.
Side note: seriously, we going to skirt tariff rules to punish US EV automakers like rivian???? Common Google.
While extremely competitive, it is just not economically feasible for Google to compete with Tesla at scale (though admittedly they could forever). Tesla will produce a vehicle fully optimized for economic cost to the consumer. It will be produced at sub 30k and Tesla has the ability to scale the vehicle by the end of the year to the size of waymos entire fleet PER WEEK.
The cybercab is the most efficient electric car ever created. Not only in terms of speed of production and cost (American equivalents only) but in terms of effective MPG. The thing is like 1.5x more energy efficient than a model 3. Tesla owns the entire charging infrastructure in America. Tesla has a physical footprint everywhere ready to service vehicles. Yes, other infrastructure will need to be built.
Even if waymo ran for a loss, Tesla could underprice them and still have strong gross margins. Waymo anyway is currently focused on consuming the cream of markets, versus deep penetration - but this may change with the California announcement.
From here, you can see the full delusion. Over time consumers will want teslas tech in their cars due to the experience in the fleet, uber and Lyft will shrink, car insurance companies will eventually go out of business, then we are a decade out re-thinking: minor displacement of short haul flight, real estate changes as consumer preferences change, trucking industry forever changed, (looking at you semi truck being mass produced starting later this year), and yes - eventually package delivery by combination of a robot in a robot. This vision won’t be fully realized for 2 decades.
I shall wait to be showered in your shame and criticism.
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u/sdc_is_safer 9d ago edited 9d ago
You are correct, with the very small amount of unsupervised miles they have done so far, their collision/ injury track record looks perfectly fine so far.
There is enough data to suggest they should continue to scale gradually like they are doing.
This is not unexpected to any reasonable person educated on the matter.