Nuro Driver
Release Notes

Q2 2024

Top 5 List

AI Model Improvements
  1. Better Performance via unification of Perception Models: By achieving unification of our geometry models including speed estimation, we’ve seen large improvements across our Perception stack. Some highlights include:
    • Improved detection of foreign objects & debris at night by 7.5%.
    • Improved tracking on uncategorized moving objects with 40% reduction in false positive tracks and 30% improvement in speed estimation errors.
  2. Smoother Pullover & Pullouts: Enabled reinforcement learning to help improve our pullover and pullout plan selection, resulting in a smoother Nuro Driver pickup and delivery experience.
  3. Enhanced Detection of Rain Intensity: We've deployed an upgraded rain detection model that activates sensor clearing, resulting in significant performance improvements:
    • Light rain recall improved by 83%
    • Heavy rain recall increased by 8%
    • Elimination of false-positive rain detections

1% Better
  1. Better Emergency Vehicle Detection: Updated Nuro Driver with a new Vision Transformer (ViT) architecture, boosting our emergency vehicle detection by 5% without any increase in false positives.
  2. Improvements in Human Traffic Controller Detection: We’ve improved the recall of human traffic controllers by 10% without any false positive regressions by leveraging our unified perception model architecture.

* All metrics are based on our internal evaluation test sets of challenging and diverse on-road and simulation scenarios.

Q1 2024

Q4 2023

Q3 2023