CO-LOCATED EVENTS

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Start-Up Lounge

1 start-up – 5 min – multiple opportunities: The most innovative start-ups showcase their services, products in a dedicated session during the conference. Don’t miss the chance to meet our selected start-ups at the end of the break in the plenary room and network with them at any time during the conference to learn moreRead more

Case Study: Enhancing safety and user trust in autonomous vehicles through generative and responsible AI

Generative AI is introducing powerful new capabilities into the automotive domain – from natural language interaction and personalized cabin experiences to dynamic simulation and predictive decision-making. However, as these systems become more integrated into safety-critical environments, the need for ethical and responsible AI practices becomes paramount. This presentation explores how generative AI can enhance bothRead more

Case Study: Virtual validation at scale – Advancing autonomous vehicle safety through software simulation and scenario scanning

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

Case Study: Safety between driving automation functions SAE L2 & L3 – A safety perspective of automated driving functions

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

Case Study: Advancing autonomous vehicle resilience through intelligent systems and standards

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

Case Study: Balancing safety-critical and less critical functions to ensuring consistent quality in emergency systems

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

Case Study: Pioneering safety in autonomous vehicles – A comprehensive approach to systematic risk mitigation

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

Case Study: Radar-based scene understanding for autonomous vehicles

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

Case Study: End-to-end AI vs. modular ADAS – Architectural trade-offs in autonomous driving

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

Case Study: The potential of Generative AI for scenario-based testing

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