powertoold
Active Member
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.
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.