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World Congress 2022 • Jun 15, 2022

Finding the unknown unknowns: intelligent data collection for autonomous driving development

Liang Yu

How do self-driving systems learn from unpredictable anomalies without uploading terabytes of junk data? Discover how intelligent edge computing captures only the critical unknown unknowns for rapid model retraining.

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#1 about 2 min

Unified tech stack and hardware for Volkswagen

An introduction to CARIAD's unified tech stack and hardware platform designed to accelerate innovation for autonomous driving functions.

#2 about 2 min

Traditional sensor data acquisition and storage challenges

The limitations of locally recording all sensor data for manual transfer and inefficient storage.

#3 about 2 min

Introducing the Big Loop intelligent data system

How the Big Loop uses isolated hardware components to safely test software and filter junk information.

#4 about 2 min

Identifying unknown unknowns in perception model scenarios

Defining corner cases like distribution shifts and rare objects that cause perception models to fail on the road.

#5 about 1 min

Methods for finding out-of-distribution perception scenarios

Comparing bayesian inference, anomaly detection, and ensemble methods for finding out-of-distribution samples.

#6 about 3 min

Filtering frames using uncertainty scores in Instinct

How the Instinct software calculates component-wise uncertainty scores on segmentation output to trigger intelligent data uploads.

#7 about 4 min

Real-world retraining and over-the-air model deployment

A pipeline demonstrating how models fail, capture triggers, retrain with auto-labeling, and deploy via over-the-air updates.

#8 about 2 min

Scaling the pioneering test fleet for data collection

Retrofitting existing vehicles enables continuous active learning and data-driven development ahead of standard deployment.

#9 about 5 min

Audience Q&A on autonomous driving models and data

Audience discussions cover handling critical safety decisions, local edge execution, dynamic uncertainty thresholds, and global training datasets.

Matching moments

2:04 min

Managing synthetic data unpredictability alongside multi-sensor autonomous vehicle deployment

Sergio Perez Sergio Perez · WWC Europe 2026

2:29 min

Enhancing automated driving through swarm data processing

Peter Bosch Peter Bosch · WWC 2024

8:55 min

Audience questions on data integration and future action models

Vijay Krishan Gupta +1 · LIVE

2:09 min

Speaker background and the need for robust models

Svetlin Penkov · LIVE

7:31 min

Addressing participant questions on liability and machine learning

Georg Kühberger +1 · LIVE

2:27 min

Creating virtual feedback cycles for in-car artificial intelligence platforms

Jan Zawadzki · WWC 2022

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