In the evolving landscape of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD), explainable AI is critical. This presentation explores the integration of explainable AI by design, offering detailed insights and actionable recommendations. Emphasizing adherence to standards like ISO PAS 8800 and Acts on AI, we highlight the necessity of robust documentation and novel testing approaches. We invite you to participate actively in the session: Join us to discuss how explainable AI can enhance transparency, trust, and compliance in the transition to software-defined vehicles.
In this session, you will learn:
- How can explainable AI principles be integrated early in the development lifecycle to align with ISO PAS 8800 and upcoming AI legislation?
- What role do advanced testing and validation methods—such as scenario-based simulation and hardware-in-the-loop—play in verifying the transparency and robustness of AI-driven ADAS functions?
- How can documentation and traceability frameworks help stakeholders demonstrate AI decision-making processes to regulators and consumers?
- What challenges do OEMs and Tier 1s face in balancing high-performance AI with explainability, and how can tools like Keysight’s Radar Scene Emulator help address them?
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