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FSD rewrite will go out on Oct 20 to limited beta

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Tesla doesn't define "HD maps". There are industry-accepted definitions of HD maps, and there hasn't been any evidence that the FSD beta ever used HD maps.

Some examples below:

End-to-end HD Mapping for Self-Driving Cars from NVIDIA Automotive

HD map | TomTom

Journal article description below:

Autonomous Driving in the iCity—HD Maps as a Key Challenge of the Automotive Industry - ScienceDirect

The necessity of HD maps for autonomous driving becomes obvious when trying to anticipate appropriate behavior in traffic beyond the sensors of a robotic car. To date, there is no sensor available that can localize and determine a car in reference to its surroundings. Although a few research projects are working on a solution based on quantum positioning, they are still in early stages, and the first prototypes are larger than a trunk of a station wagon. It will take a few more years before this quantum physics technology is ready for use [7]; therefore, autonomous driving relies on dynamic HD maps. Localization is ensured by the mapping of HD map data with landmarks such as buildings as reference positions. The position of a car in relation to various landmarks provides an exact localization. The next move is the integration of HD mapping in series of cars [8].

The sensor data collected by thousands of cars allows the establishment of dynamic HD maps with high accuracy and real-time information. With this kind of self-learning cloud service, the latest updates can be sent to all registered cars over a 4G cellular connection. The more cars participate, the more precise the HD map cloud solution will become.
 
Tesla's internal map resolution is actually fairly low, but they up-sample and interpolate the data for improved aesthetics.

Here's a view of the raw data:

upload_2020-12-17_19-50-7.png
 
As this thread now is about our favorit topic HD map, I remembered that I used to be a part of the group defining the ADASISv3 standard. Unfortuneatly Tesla was not a member of this group:
Members | new adasis website

Just to catch up a bit, I found this video, maybe you HD vs SD maps experts will like it:
How HD maps and ADASIS v3 can extend the vision of automated vehicles | Automotive World

Seems like not much has changed since I was involved ~4 years ago. So I guess Tesla was right to not be a part of it and instead do their own solution.
 
Tesla doesn't define "HD maps". There are industry-accepted definitions of HD maps, and there hasn't been any evidence that the FSD beta ever used HD maps.

Some examples below:

End-to-end HD Mapping for Self-Driving Cars from NVIDIA Automotive

HD map | TomTom

Journal article description below:

Autonomous Driving in the iCity—HD Maps as a Key Challenge of the Automotive Industry - ScienceDirect

The necessity of HD maps for autonomous driving becomes obvious when trying to anticipate appropriate behavior in traffic beyond the sensors of a robotic car. To date, there is no sensor available that can localize and determine a car in reference to its surroundings. Although a few research projects are working on a solution based on quantum positioning, they are still in early stages, and the first prototypes are larger than a trunk of a station wagon. It will take a few more years before this quantum physics technology is ready for use [7]; therefore, autonomous driving relies on dynamic HD maps. Localization is ensured by the mapping of HD map data with landmarks such as buildings as reference positions. The position of a car in relation to various landmarks provides an exact localization. The next move is the integration of HD mapping in series of cars [8].

The sensor data collected by thousands of cars allows the establishment of dynamic HD maps with high accuracy and real-time information. With this kind of self-learning cloud service, the latest updates can be sent to all registered cars over a 4G cellular connection. The more cars participate, the more precise the HD map cloud solution will become.

Hd maps consists of geometeric and/or semantic maps. While Tesla HD map doesn't have a geometric layer. Their map does have a semantic layer.

Rethinking Maps for Self-Driving

1*novXPga1nTb5aI1g9_-ReQ.png
 
Hd maps consists of geometeric and/or semantic maps. While Tesla HD map doesn't have a geometric layer. Their map does have a semantic layer.

Rethinking Maps for Self-Driving

1*novXPga1nTb5aI1g9_-ReQ.png

Tesla fsd beta doesn't use HD maps, period.

From your article:

These HD maps need to represent the world at an unprecedented centimeter resolution, which is one to two orders of magnitude greater than the roughly meter level resolution that web map services offer today.
 
Tesla fsd beta doesn't use HD maps, period.

From your article:

These HD maps need to represent the world at an unprecedented centimeter resolution, which is one to two orders of magnitude greater than the roughly meter level resolution that web map services offer today.

Again it seems like you don't undersand.
HD map is just a term that covers multiple layers.
The only layer that requires CM accuracy is the geometric layer.
The semantic layer isn't cm accurate nor does it need to be.
 
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Again it seems like you don't undersand.
HD map is just a term that covers multiple layers.
The only layer that requires CM accuracy is the geometric layer.
The semantic layer isn't cm accurate nor does it need to be.
Here comes the HD Map brigade.

The basic question is scalability. Tesla usage of maps is highly scalable, Waymo's is not. End of story.