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As AV technology advances toward mass production, the complexity of validating safety across countless real-world scenarios grows exponentially. Traditional physical testing methods are no longer sufficient to ensure the reliability of AV systems under diverse and unpredictable conditions. This presentation will explore how advanced software simulation, combined with large-scale scenario scanning, enables comprehensive validation ofRead more

As driving automation systems advance in complexity, the gap between SAE Level 2 and Level 3 presents significant challenges – not only for manufacturers implementing increasingly stringent and sometimes overlapping regulations, but also for users who are expected to understand and appropriately operate these technologies. Recent incidents involving Level 2 driver assistance functions reveal aRead more

AI is at the core of autonomous driving, powering perception, decision-making, and now – safety assurance. This presentation explores how AI enhances AV resilience and safety, both as a functional enabler and as a tool for safety analysis. We’ll introduce ISO 8800, the emerging standard for AI safety in automotive systems, and discuss its integrationRead more

As AVs transition from research labs to public roads, ensuring the reliability of safety-critical functionalities, such as emergency braking, becomes paramount. These systems must operate with uncompromising quality and consistency, regardless of the complexity or number of other vehicle functions running in parallel. This presentation explores strategies to maintain the integrity of safety-critical systems whileRead more

As autonomous vehicles progress toward widespread deployment, ensuring their safety is paramount. a comprehensive approach to system safety, focusing on methods to identify, assess, and mitigate risks across the entire autonomous driving technology stack considers rigorous safety protocols at every stage of development and deployment, from safety-critical sensor fusion to fail-safe mechanisms and real-time decision-making. TheRead more

The perception and classification of moving objects are crucial for autonomous vehicles performing collision avoidance in dynamic environments. LiDARs and cameras tremendously enhance scene understanding but do not provide direct motion information and face limitations under adverse weather. Radar sensors work under these conditions, including rain, fog, and snow, and provide Doppler velocities, delivering direct informationRead more

This talk examines the core architectural choices in autonomous driving: modular, model-based ADAS versus end-to-end deep learning. Modular systems offer interpretability and compatibility with safety standards like ISO 26262, while end-to-end approaches promise greater adaptability through data-driven learning. However, the latter challenges current validation and certification frameworks. We explore technical trade-offs, real-world deployment implications, andRead more

Verification and validation processes play a vital role in ensuring the safety and reliability of automated driving. Scenario-based testing has emerged as an effective method for identifying critical scenarios that challenge the capabilities of automated driving systems. This presentation aims to explore how to leverage the potential of Generative AI for traffic scenario generation. TheRead more

Ensuring the safety of AI in safety-critical systems is essential for the deployment of automated driving technology. While AI has demonstrated its potential to surpass classical approaches in handling complexity and enabling higher levels of autonomy, the necessary safety assurance frameworks remain underdeveloped. This presentation will provide a forward-looking perspective on the interdependencies between AIRead more

Imagine a self-driving car navigating a busy city street. It detects pedestrians, reacts to sudden obstacles, and ensures passenger safety – all in milliseconds. But behind the scenes, hidden from view, lies an invisible force that makes it all possible: the C and C++ compilers and libraries that transform complex ADAS software into machine-executable code.Read more