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World Congress 2023 • Aug 11, 2023

Automated Driving - Why is it so hard to introduce

Sayed Bouzouraa

When a decelerating car pitches downward, sensors can scan too low and detect ghost objects. Learn why overcoming closed-loop perception challenges requires radically restructuring legacy automotive engineering teams.

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#1 about 6 min

The reality gap between self-driving concepts and availability

A personal story highlights the discrepancy between marketing concepts and actually available autonomous vehicles.

#2 about 2 min

Audi progressive milestones in automated driving and perception

Previous historical autonomous projects reveal the evolution and complexities of shifting driving responsibility to the vehicle.

#3 about 6 min

Transitioning product focus from assisted to automated driving

Assisted driving is reaching performance saturation while automated functionality introduces disruptive challenges regarding responsibility shifts.

#4 about 3 min

Proving positive risk balance against human highway performance

Releasing an autonomous system requires proving safety and legal compliance that surpasses human highway driving statistics.

#5 about 5 min

Discovering and sharing edge cases for automated driving

A proposed marketplace for sharing safety-critical edge cases helps models tackle complex environmental variables.

#6 about 6 min

Interpreting raw sensor data and targeting anomaly detection

Lidar and camera vulnerabilities emphasize the need for targeted anomaly detection rather than fully estimating open-loop environments.

#7 about 2 min

Managing closed-loop system reactions to ghost object artifacts

Reacting to false environmental artifacts changes vehicle pitch angles and creates self-confirming radar detection loops.

#8 about 4 min

Adapting organizational structures for autonomous systems engineering teams

Cross-functional event-chain teams replace traditional departmental silos to better manage complex dependencies across vehicle hardware components.

#9 about 2 min

Addressing ethical dilemmas and automotive technology market competitiveness

Collecting specific scenario data addresses ethical edge cases while established safety engineering provides a regional competitive advantage.

Matching moments

2:50 min

Navigating the levels of vehicle autonomy

Ulrich Wurstbauer +1 · LIVE

1:19 min

Advancing autonomous driving capabilities with specialized software talent

Katrin Lehmann Katrin Lehmann +1 · Coffee With Developers

12:18 min

Audience questions on self driving evolution and legal progress

Hans-Jürgen Eidler · LIVE

3:05 min

Introduction to the speakers and topic

Ulrich Wurstbauer +1 · LIVE

4:55 min

Audience Q&A on autonomous driving models and data

Liang Yu · WWC 2022

2:38 min

Differences between levels of automated driving responsibilities

Lukas Sucher Lukas Sucher +1 · WWC 2024

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