CPU and GPU Performance: How can automotive CPUs and GPUs be optimized to deliver the massive computational power needed for autonomous driving tasks, such as real-time sensor processing and AI algorithms, while keeping power consumption manageable?

Enabling efficient & secure delivery of the SDV: Rethinking delivery models from agile to DevOps to DevSecOFPGA Customization and Flexibility: How can FPGAs be effectively used to accelerate specific autonomous vehicle tasks (e.g., real-time data processing, sensor fusion) while maintaining the flexibility to adapt to evolving software and algorithmic requirements?

Sensor Fusion Units: How can sensor fusion hardware efficiently combine data from LiDAR, radar, cameras, and ultrasonic sensors to provide a unified, accurate, and low-latency perception of the environment?

critical functions like steering, braking, and acceleration in a real-time, deterministic manner, especially with high levels of autonomy?

Drive-By-Wire Systems: How can robust, reliable drive-by-wire systems be developed to replace traditional mechanical linkages (steering, throttle, brake) with electronic controls, while ensuring safety, redundancy, and fast response times?

Low-Latency Data Processing: How can real-time processing of data, including perception, planning, and decision-making, be ensured across the hardware stack (CPUs, GPUs, FPGAs) with ultra-low latency for safe autonomous vehicle operation?

Communication Systems (V2X): How can vehicle-to-everything (V2X) communication hardware be designed to enable fast, secure, and reliable data exchange between vehicles, infrastructure, and other road users, while managing the challenge of high data throughput and low-latency networking?

Virtualization: What role do virtual software platforms play in SDV? How they accelerate product development and testing?

Energy Efficiency in Computing Hardware: How can high-performance CPUs, GPUs, and other processing units be designed or optimized to balance the demanding computational needs of autonomous driving with the vehicle’s overall energy budget, particularly for electric vehicles?

Hardware Redundancy and Failover Mechanisms: How can critical onboard computing hardware and control systems be designed with redundancy to ensure safe operation in the event of hardware failure or component malfunction?

Integration of Control and Compute Systems: What are the best strategies for integrating compute-heavy systems (AI/ML, sensor processing) with real-time control systems (drive-by-wire, braking, steering), ensuring seamless and coordinated operation without introducing bottlenecks?