FSD Beta 11.3.1 (2022.45.10) Official Tesla Release Notes

– Enabled FSD Beta on highway. This unifies the eyesight and arranging stack on and off-freeway and replaces the legacy highway stack, which is over four several years aged. The legacy freeway stack nevertheless depends on numerous solitary-camera and one-body networks, and was setup to deal with very simple lane-distinct maneuvers. FSD Beta’s multi-digital camera movie networks and subsequent-gen planner, that makes it possible for for much more advanced agent interactions with much less reliance on lanes, make way for including a lot more clever behaviors, smoother regulate and far better determination generating.

– Added voice generate-notes. After an intervention, you can now mail Tesla an anonymous voice message describing your experience to assistance enhance Autopilot.

– Expanded Automated Crisis Braking (AEB) to cope with motor vehicles that cross ego’s path. This contains situations the place other autos operate their red light-weight or turn throughout ego’s path, thieving the right-of-way. Replay of prior collisions of this variety implies that 49% of the events would be mitigated by the new conduct. This enhancement is now lively in equally handbook driving and autopilot procedure.

– Enhanced autopilot response time to crimson light runners and halt indication runners by 500ms, by greater reliance on object’s instantaneous kinematics along with trajectory estimates.

– Added a prolonged-range highway lanes community to help earlier reaction to blocked lanes and substantial curvature.

– Minimized purpose pose prediction mistake for prospect trajectory neural network by 40% and reduced runtime by 3X. This was realized by strengthening the dataset utilizing heavier and additional strong offline optimization, raising the dimension of this improved dataset by 4X, and utilizing a far better architecture and feature area.

– Enhanced occupancy network detections by oversampling on 180K difficult videos which includes rain reflections, road particles, and superior curvature.

– Improved remember for shut-by reduce-in situations by 20% by introducing 40k autolabeled fleet clips of this situation to the dataset. Also improved dealing with of lower-in instances by improved modeling of their motion into ego’s lane, leveraging the same for smoother lateral and longitudinal command for lower-in objects.

– Included “lane direction module and perceptual reduction to the Road Edges and Lines network, improving upon the absolute recall of strains by 6% and the complete remember of highway edges by 7%.

– Improved total geometry and steadiness of lane predictions by updating the “lane advice” module representation with details appropriate to predicting crossing and oncoming lanes.

– Enhanced managing via substantial speed and substantial curvature situations by offsetting towards inner lane strains.

– Improved lane changes, including: earlier detection and managing for simultaneous lane adjustments, improved hole collection when approaching deadlines, better integration in between speed-based and nav-based mostly lane adjust conclusions and more differentiation concerning the FSD driving profiles with respect to velocity lane modifications.

– Improved longitudinal manage reaction smoothness when pursuing guide automobiles by better modeling the probable outcome of guide vehicles’ brake lights on their long run pace profiles.

– Improved detection of rare objects by 18% and reduced the depth error to huge vans by 9%, mostly from migrating to far more densely supervised autolabeled datasets.

– Enhanced semantic detections for faculty busses by 12% and cars transitioning from stationary-to-driving by 15%. This was obtained by bettering dataset label precision and expanding dataset sizing by 5%.

– Improved conclusion earning at crosswalks by leveraging neural community centered ego trajectory estimation in spot of approximated kinematic products.

– Improved dependability and smoothness of merge handle, by deprecating legacy merge area 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 publish scheduling across twin SOCs.