Tuesday, July 23, 2024
HomeTeslaTesla Releases Full Self-Driving (FSD) Beta 11.3.1 to Non-Tesla Staff — Tesla...

Tesla Releases Full Self-Driving (FSD) Beta 11.3.1 to Non-Tesla Staff — Tesla House owners of Silicon Valley



  • Enabled FSD Beta on freeway. This unifies the imaginative and prescient and planning stack on and off-highway and replaces the legacy freeway stack, which is over 4 years previous. The legacy freeway stack nonetheless depends on a number of single-camera and single-frame networks and was set as much as deal with easy lane-specific maneuvers. FSD Beta’s multi-camera video networks and next-gen planner, which permits for extra complicated agent interactions with much less reliance on lanes, make approach for including extra clever behaviors, smoother management, and higher decision-making.

  • Improved recall for close-by cut-in circumstances by 15%, significantly for giant vehicles and high-yaw fee eventualities, by means of a further 30k auto-labeled clips, mined from the fleet. Moreover, expanded and tuned devoted pace management for cut-in objects.

  • Improved the place of ego in vast lanes, by biasing within the route of the upcoming flip to permit different vehicles to maneuver round ego.

  • Improved dealing with throughout eventualities with excessive curvature or giant vehicles by offsetting in lanes to take care of protected distances to different autos on the highway and enhance consolation.

  • Improved habits for path blockage lane adjustments in dense visitors. Ego will now keep extra headway in blocked lanes to hedge for potential cans in dense visitors.

  • Improved lane adjustments in dense visitors eventualities by permitting greater acceleration in the course of the alignment section, This leads to extra pure hole choice to overhaul adjoining lane autos very near ego

  • Made turns smoother by bettering the detection consistency between lanes, strains, and highway edge predictions. This was achieved by integrating the most recent model of the lane steerage module into the highway edge and features community.

  • Improved accuracy for detecting different autos’ shifting semantics. Improved precision by 23% for circumstances the place different autos transition to driving and decreased error by 12% for circumstances the place Autopilot incorrectly detects its lead car as parked. These have been achieved by growing video context within the community, including extra knowledge on these eventualities, and growing the loss penalty for control-relevant autos.

  • Prolonged most trajectory optimization horizon, leading to smoother management for top curvature roads and much away autos when driving at freeway speeds.

  • Improved driving habits subsequent to rows of parked vehicles in slim lanes, preferring to offset and keep inside lane as a substitute of unnecessarily lane altering away or slowing down.

  • Decreased false offsetting round objects in vast lanes and close to intersections by bettering object kinematics modeling in low-speed eventualities.

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