mikes_fsd
Banned
Exactly!so HD maps are bad but high precision maps are good? did I get it right?
That was exhausting!
Context is your friend!
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FSD rewrite will go out on Oct 20 to limited beta
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That was exhausting!
Context is your friend!
mikes_fsd
Banned
Just like in 2005 today's maps would be considered HD.
I am going to offer up the following for a definition that separate HD Maps (hard to maintain) vs High Precision Map (as proposed by Tesla in 2015, today is just normal map data in your Google Maps).
If maps require any pre-rendered tiles of surroundings to be fed into the NN, they are HD maps. They are used as foundation for the NN's processing. They take time to capture, process and maintain on top and are a separate feed from the navigational maps.
Hight Precision Maps are not pre-rendered maps, they are fed into the NN's and are used in conjunction with other feeds but are not the baseline for the output. The same map data is used for navigation as well.
Hope it could work as a delineator in the definitions.
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Maps is the wrong term to use I guess.
Waymo creates a full 3D reconstruction of every road, offline, that then is available to it's cars to compare against real-time 3D reconstruction.
Tesla probably feeds in some basic map knowledge (coordinates of intersection objects, street structures?) of roads and intersections into its real-time algorithm for 3D reconstruction.
Tesla does not create a full 3-D reconstruction of the environment offline for comparison.
Waymo creates a full 3D reconstruction of every road, offline, that then is available to it's cars to compare against real-time 3D reconstruction.
Tesla probably feeds in some basic map knowledge (coordinates of intersection objects, street structures?) of roads and intersections into its real-time algorithm for 3D reconstruction.
Tesla does not create a full 3-D reconstruction of the environment offline for comparison.
mikes_fsd
Banned
Maybe this is the best way to delineate.
HD Maps have a pre-rendered environment that must be reconciled with the perceived reality that is output by the NN!
Does that work?
As it should be and as Tesla has stated that they use maps.
How is navigation supposed to be done in a FSD car if the car does not have maps?
The argument is not on whether maps are used, the argument is that it is not HD Maps (not highly detailed cm level accuracy maps)
In 2015 a full year before Tesla revealed the Autopilot 2.0 hardware.. there was this article Tesla Building Next Gen Maps through its Autopilot Drivers
How Tesla was getting fleet data to improve the accuracy of maps. At that time not many providers had lane level info for navigation (Google maps had just introduced the lane level info in their turn-by-turn navigations)
This does not give you lane marking drawn on tiles.
It gets you info along the lines of: 4 lanes in one direction off-ramp starts at this geo-code, etc
Just remember that this mapping effort was one of the things that delayed FSD, Elon said that that got them to "local maximums" and that they had to abandon the high precision mapping and go back to relying on vision to make further progress.
Also, by definition anything that requires pre-existing maps, of any resolution, can not ever be L5. Because L5 has to be able to drive on a brand new freshly paved, or dirt/gravel, road. And we have seen examples of the Tesla beta FSD driving on roads that aren't even in Google Maps yet.
mikes_fsd
Banned
Oh I know that.
They realized Maps (HD or otherwise) cannot be the foundation. Vision has to be the foundation and map data is just another input that enhances the final output.
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At least looking at OpenStreetMap data, intersections with traffic lights and stop signs often have a single node (e.g., the point where two road lines cross) with an attribution tag indicating there is a given road feature. If we just assume most intersections are of 2 lanes in each direction with roughly 5 meters width for each lane, the sign or signal most likely is along the edge or corner of the intersection (and not in the exact middle of the road), so the accuracy is probably around 5-10 meters for a small intersection. And this is based on some human overlaying a line on top of an ideally somewhat reasonably GPS oriented satellite image.
Another way to think about this is the actual data structures needed to encode OSM/Tesla map data vs "HD maps." From a quick search, HD maps generally have relatively precise 3D positioning and adjacency data for every single lane subsegment and sign/signal whereas OSM 2D vector map data has points, lines and areas that have coarse locations with tags. It's not uncommon in OSM for a 4-lane road to be identified with a single line with an attribution of lanes=4 vs a HD map would have information about each of the 4 lanes including where the lane gets wider or narrower.
how can maps be not-prerendered? Maps is a prior knowledge you have of the area before you actually enter the area.
You might want to rethink your definition a bit.
I'm interested in knowing what's being compared in this exchanging of outputs. There's so much noise watching the visualization with edges jumping around that you'd think a disagreement would occur quite frequently. Both road features and path planning (sometimes flipping from right/left turn) seem unstable.
It's possible this is not enabled yet, but I was also hoping the rewrite fourth dimension (time) would add some stability to features disappearing.
they do, but it's not clear if everybody got the explicit permission to post their stuff or only some of the participants.
mikes_fsd
Banned
They are not creating a 3D environment offline.
My guess is they are taking some simplistic information about the intersection, and predicting what it should look like based on learnings of intersections in general. Thus the output looks quite realistic, though it is actually mostly a prediction.
I’ve been following along, and at this point, you’re coming off as purely a contrarian with comments like this.
mikes_fsd
Banned
The easiest thing for them to use would be a vector tile. After all that computers just doing a bunch of math.
mikes_fsd
Banned
yes, that's what Tesla does. They use valhalla/mapbox container with tiles.
Millimeter precision HD Vector Maps (the title of that page is fun btw)
Here's Tesla fork of the code in their own github: teslamotors/valhalla
This commit is support for loading gzipped tiles: support loading gzipped tiles · teslamotors/valhalla@23e08fc
they then feed these vectors and other features along the route into the NN.
So by not pre-rendered you mean vector tiles? You should have used this term then.
flat fixed resolution "pixel" tiles are useless anyway - you cannot easily scale them you cannot know easily what's on them without machine vision (that needs to basically convert it back into the vector form) and so on. Ican't think of anybody doing this.
Now I am not sure you can call lidar 3D world scans "pre-rendered"/"raster" because I have no idea how they actually store that stuff.
They don't. We did not really discuss anything about 3D in prior discussion, why bring in 3D in all of a sudden?
Yes, this is what they do. Most importantly, if something is not in that "simplistic" information set as you call it (like say there's no side street marked in there) - the system does not see it until it's right next to it and even then it's not very realistic (see the SC road link I posted for examples) to have actual high confidence visual. When something IS marked in the "simplistic information" set - the system "predicts" it based on a lot lower confidence visuals.
huh? what's contrarian about it? I am just trying to get a non-contradictory definition.
mikes_fsd
Banned
So, you are going to claim the vector tiles - something that Google has used on all they maps since 2013 is the HD Maps that you are referring to when you say Tesla uses HD Maps?
Am I understanding you correctly?
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