It's not that simple though. What so you consider "data" when it comes to self driving cars? Waymo collects high resolution data with every car (multiple GB or possibly TB of data per car per day).
Tesla hasn't sent very high resolution data back home yet. Though they are looking to get video from customers now to help make this go faster[0].
So while Tesla has more vehicles on the road, that doesn't mean they are getting better data for self driving car research.
They may not be sending data back home via the mobile network, but you can bet your boots they make exhaustive logs of Autopilot disengagements and store them locally to be siphoned off at the next service.
I wonder if they have WiFi base stations collecting data at Supercharger points? That's what I'd do.
That would still be only one slice of the many many situations you need to master, and that Waymo already has. E.g. something as simple as entering and exiting a small roundabout, like that YouTube video showed a Tesla couldn't do. Miles driven by Tesla owners aren't purposefully looking for those situations when they engage autopilot.
Are you sure? Again this is just how I'd do things, but after I had a bunch of disengagement snapshots, the next thing I'd do is start taking snapshots of similar situations. We live in an age of easy and super-accurate image classification, it wouldn't be too hard to start a snapshot every time the front camera view contains a roundabout.
What I'm trying to say is that the number of cars on the road and miles driven aren't what matter to their autopilot learning, when compared to other self-driving companies. Most people use their car to go places comfortably, not to look out for learning experiences for Tesla.
With how long commutes are in the US, a very very small fraction of miles driven by people on autopilot will be other than "the car was already on the highway, autopilot changed lanes a few times, and after a while was manually disengaged to take an exit".
That small fraction is what could be compared with the miles and number of cars driven by the other companies, because in the latter case it's hired drivers actively looking for conditions of interest to the engineers.
I definitely wouldn't be happy about Tesla uploading gigabytes of data on my metered connection. Even if it was unmetered, most people don't have very fast up-speeds and that could take days to upload and heavily impact their speeds. Absolutely unacceptable.
Do owners generally connect their cars to their home wifi? (I don't know, is this a thing with Teslas?)
Even if so, uploading gigabytes of data every day is going to be noticed. While I'm sure they have the legal right to do so (via their TOS / EULA) they probably still don't want to emphasize that they're gathering that much data (unless you opt in to their fleet learning stuff).
>Do owners generally connect their cars to their home wifi?
Generally I think they do to access the Tesla App features. Tesla also have a network connection so they may already be uploading the information anyway over cell networks.
Teslas do connect to LTE. Why would they pay that much for a data plan? In the US, you can get mobile hotspot plans for $3/month + $10/gbyte. That's the consumer price; wholesale over 100s of thousands of cars has got to be cheaper.
Machine vision is usually an exercise in data reduction. Greyscale is typically used in most computer vision applications, so it may be the case that Waymo has more information but that is not necessarily of any benefit.
Tesla hasn't sent very high resolution data back home yet. Though they are looking to get video from customers now to help make this go faster[0].
So while Tesla has more vehicles on the road, that doesn't mean they are getting better data for self driving car research.
[0] https://electrek.co/2017/05/06/tesla-data-sharing-policy-col...