EVNow
Well-Known Member
They could have done that instead of slashing prices - anyway, now that Model Y cap is 80K, they can increase the price further but offer this incentive. May be offer the incentive with higher priced trims.
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FSD Beta 10.69
- Thread starter Buckminster
- Start date
Lol. It's called a Michigan left, I suppose because it was invented there? They started putting them in Tucson a few years ago. Maybe someone in the roads department came from Michigan. Most of those people are snowbirds who only come for the winter, but their left turns are with us year round.
Knightshade
Well-Known Member
No worries. This is the latest release of the holiday update software version, and 2022.44.30.10 includes FSD beta if you purchased or subscribe to FSD. It's the version I am running now along with many others.
If you want further confirmation, feel free to check Teslascope or TeslaFi.
KArnold
Active Member
The other day I'm on local interstate doing about 70 MPH. I'm taking my exit where I know I'll be likely at a red light in 800 feet. So I manually dial down the speed dramatically. As the car was slowing it switched from AP back to FSDb. In that same instance we went from a normal, foot-off-accelerator deceleration to little more than coasting. It's significantly different.
My original thought was they were trying to limit FSDb manual speed setting. If so that would not be right but I misunderstood. Looks like it's the "too slow to slow" issue.
My original thought was they were trying to limit FSDb manual speed setting. If so that would not be right but I misunderstood. Looks like it's the "too slow to slow" issue.
That's what I had just before I got 2022.44.30.10. The latter seems to be a very minor update, and many of us only got it by proactively going to the car Software menu to check for updates. If you didn't do that, it's not surprising that it's taken several weeks for it to show up. There's no downside to it that I see, but don't expect any miracles either.
Knightshade
Well-Known Member
What's weird is you'd think Tesla would stop pushing out any existing version since they're under recall-- even if it's updating someone from a slightly older recall version to a slightly newer one.
If I had to guess, the law actually requires them to block such things, but nobody at Tesla bothered to do it.
If I had to guess, the law actually requires them to block such things, but nobody at Tesla bothered to do it.
sleepydoc
Well-Known Member
Not sure about that - if the minor point release is to correct other bugs or potential safety issues and they are still before the time frame in which they're required to have the recall fix ready then it makes sense to issue the update. It's theoretically not worsening the problem, just fixing other problems.
Knightshade
Well-Known Member
The recall announcement says it covers "All versions of FSD Beta leading up to the version that contains the recall remedy"
AFAIK once something is recalled you can't keep giving it to new people... indeed there's a line required in the notice specifically saying how and when it was (past tense) fixed in production of new product.... In this case Teslas answer is simply that new cars don't get the beta software during manufacturing at all.
OTOH it does also mention there are some "pending" installs- so maybe these folks had pending already DLed ones and Tesla did not do anything to prevent those from installing-- that'd be distinct from new folks getting any current recalled version pushed to them since the announcement so that might explain it.
Until the new release, I could see ending FSD downloads to new customers if the goal is to maximize safety.
NHTSA should take advantage of OTA since it's much easier to control versus mechanical issues like defective air bags where a customer need to be tracked down, informed, and encouraged to schedule a service appointment.
sleepydoc
Well-Known Member
But if it’s just a point release fixing other unrelated bugs and not introducing any new software it doesn‘t matter. Essentially the update is keeping portions that NHTSA is concerned with unchanged. That’s the whole point. (Pun intended)
FSDtester#1
Craves Electrolytes
FSD Beta 11.3 Release Notes
— Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
— Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
— Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
— Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
— Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
— Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
— Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
— Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
— Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
— Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
— Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
— Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines.
— Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
— Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
—Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
— Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
— Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
— Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
— Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs
— Enabled FSD Beta on highway. This unifies the vision and planning stack on and off-highway and replaces the legacy highway stack, which is over four years old. The legacy highway stack still relies on several single-camera and single-frame networks, and was setup to handle simple lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, that allows for more complex agent interactions with less reliance on lanes, make way for adding more intelligent behaviors, smoother control and better decision making.
— Added voice drive-notes. After an intervention, you can now send Tesla an anonymous voice message describing your experience to help improve Autopilot.
— Expanded Automatic Emergency Braking (AEB) to handle vehicles that cross ego’s path. This includes cases where other vehicles run their red light or turn across ego’s path, stealing the right-of-way.
— Replay of previous collisions of this type suggests that 49% of the events would be mitigated by the new behavior. This improvement is now active in both manual driving and autopilot operation.
— Improved autopilot reaction time to red light runners and stop sign runners by 500ms, by increased reliance on object’s instantaneous kinematics along with trajectory estimates.
— Added a long-range highway lanes network to enable earlier response to blocked lanes and high curvature.
— Reduced goal pose prediction error for candidate trajectory neural network by 40% and reduced runtime by 3X. This was achieved by improving the dataset using heavier and more robust offline optimization, increasing the size of this improved dataset by 4X, and implementing a better architecture and feature space.
— Improved occupancy network detections by oversampling on 180K challenging videos including rain reflections, road debris, and high curvature.
— Improved recall for close-by cut-in cases by 20% by adding 40k autolabeled fleet clips of this scenario to the dataset. Also improved handling of cut-in cases by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal control for cut-in objects.
— Added “lane guidance module and perceptual loss to the Road Edges and Lines network, improving the absolute recall of lines by 6% and the absolute recall of road edges by 7%.
— Improved overall geometry and stability of lane predictions by updating the “lane guidance” module representation with information relevant to predicting crossing and oncoming lanes.
— Improved handling through high speed and high curvature scenarios by offsetting towards inner lane lines.
— Improved lane changes, including: earlier detection and handling for simultaneous lane changes, better gap selection when approaching deadlines, better integration between speed-based and nav-based lane change decisions and more differentiation between the FSD driving profiles with respect to speed lane changes.
— Improved longitudinal control response smoothness when following lead vehicles by better modeling the possible effect of lead vehicles’ brake lights on their future speed profiles.
—Improved detection of rare objects by 18% and reduced the depth error to large trucks by 9%, primarily from migrating to more densely supervised autolabeled datasets.
— Improved semantic detections for school busses by 12% and vehicles transitioning from stationary-to-driving by 15%. This was achieved by improving dataset label accuracy and increasing dataset size by 5%.
— Improved decision making at crosswalks by leveraging neural network based ego trajectory estimation in place of approximated kinematic models.
— Improved reliability and smoothness of merge control, by deprecating legacy merge region tasks in favor of merge topologies derived from vector lanes.
— Unlocked longer fleet telemetry clips (by up to 26%) by balancing compressed IPC buffers and optimized write scheduling across twin SOCs
clydeiii
Member
ONLY when or IF it was released. We have had V11 Release Notes 2 times already from last year.
There's so much to glean from this list. One that stands out is adding a mystery offset for sharp turns in an attempt to favor the inner lane line. What could possibly go wrong with that?
And gaining 500ms response time for red light/stop sign runners on AP by using an object's instantaneous kinematics and trajectory. Gotta wonder how noisy those instantaneous kinematics are and their added risk for false alarms. I imagine there's still more 500ms delays to be found.
This will be an eventful release.
oh great, now its going to start being timid at traffic lights when it overreacts to cars on either side.
Also notice nothing about improving random slowdowns or giving choices about lane changes, just giving more of a difference for speed based lane changes. I just want it to warn me before just signaling and changing lanes for no reason.
That's what I've been hoping for, and with an audio signal, not just one of the next-to-useless text warning bars below the ego car. But as I posted elsewhere, better responsiveness to the Chill behavior should help.
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