Tesla’s new Full Self-Driving Beta update (10.13) is all about left turns, animal detection, speed limits, and much more. Here are the release notes.
FSD Beta enables Tesla vehicles to drive autonomously to a destination entered in the car’s navigation system, but the driver needs to remain vigilant and ready to take control at all times.
Since the responsibility lies with the driver and not Tesla’s system, it is still considered a level two driver-assist system despite its name. It has been sort of a “two steps forward, one step back” type of program, as some updates have seen regressions in terms of the driving capabilities.
Tesla has frequently been releasing new software updates to the FSD Beta program and adding more owners to it.
The last update came in May, so it has been a little while since Tesla has pushed something new to the FSD Beta fleet.
Last week, we reported on CEO Elon Musk talking about the new FSD Beta 10.13 update, which he said would be released internally last weekend and externally this week.
The release notes have now leaked and they show what Tesla has been working on for this update (via Reddit):
- Improved decision making for unprotected left turns using better estimation of ego’s interaction with other objects through the maneuver.
- Improved stopping pose while yielding for crossing objects at “Chuck Cook style” unprotected left turns by utilizing the median safety regions.
- Made speed profile more comfortable when creeping for visibility, to allow for smoother stops when protecting for potentially occluded objects.
- Enabled creeping for visibility at any intersection where objects might cross ego’s path, regardless of presence of traffic controls.
- Improved lane position error by 5% and lane recall by 12% with a (snipped…?)
- Improved lane position error of crossing and merging lanes by 22% by adding long-range skip connections and a more powerful trunk to the network architecture.
- Improved pedestrian and bicyclist velocity error by 17%, especially when ego is making a turn, by improving the onboard trajectory estimation used as input to the neural network.
- Improved animal detection recall by 34% and decreased false positives by 8% by doubling the size of the auto-labeled training set.
- Improved detection recall of far away crossing vehicles by 4% by tuning the loss function used during training and improving label quality.
- Improved the “is parked” attribute for vehicles by 5% by adding 20% more examples to the training set.
- Upgraded the occupancy network to detect dynamic objects and improved performance by adding a video module, tuning the loss function, and adding 37k new clips to the training set.
- Reduced false slowdowns around crosswalks by better classification of pedestrians and bicyclists as not intending to interact with ego.
- Reduced false lane changes for cones or blockages by preferring gentle offsetting in-lane where appropriate.
- Improved in-lane positioning on wide residential roads.
- Improved object future path prediction in scenarios with high yaw rate.
- Improved speed limit sign accuracy on digital speed limits by 29%, on signs with difficult relevance by 23%, on 3-digit speeds by 39%, and on speed limit end signs by 62%. Neural network was trained with 84% more examples in the training set and with architectural changes which allocated more compute in the network head (snipped…?)
As Musk said last week, there is a clear focus on this update to better handle handle left turns, especially the difficult left turn that early FSD Beta tester Chuck Cook has been putting the software through for the last year and a half.
But we now learn that the update also makes some other improvements including animal detection, speed limit sign reading, and more.
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Author: Fred Lambert