AI, Machine Learning, Neural Networks, Deep Driving & Cognitive Vehicles

• The most state of the art algorithms for computer vision and machine learning
• Role of Deep Neural Networks (DNN) in self-driving cars, associated challenges and level of traceability
• Implications of machine learning for functional safety
• Implementing end-to-end learning and/or hybrid approaches & access to real-time data and decision logs
• Key challenges in AI and perception technologies for autonomous vehicles

Virtual & Real Life Testing, Validation & Simulation

• Latest research in advanced, large-scale testing of autonomous vehicles and validation methods
• The challenges behind using synthetic data for validation & using virtual kilometers (simulations, HIL/SIL) as an acceptable industry validation method
• When to use simulation, when not and looking at how edge cases define the development of autonomous vehicles

Autonomous Vehicle Software Architectures, Deep Learning Architectures, Highly Scalable Architectures & AV Platforms

• Scaling up autonomous vehicle system architectures
• Using vehicle architectures to solve the functional safety need
• From fail-safe to fail-operational architectures & flexible fusion architectures
• Developing & testing of fail-operational automated driving architectures
• Latest concepts, challenges, use cases & game changers to the new AUTOSAR Adaptive Platform for Connected and Autonomous Vehicles

Autonomous Shuttles, Commercial Vehicles, Trucking Automation, Platooning & Deployment

• Driving Decision-Making Approach for Autonomous Shuttles, Robotaxis & Trucking Platoons
• Key challenges in the Cybersecurity of Autonomous Vehicle Platooning
• Results and challenges from the early deployment of autonomous shuttles and autonomous platoons – data & future research requirements?
• V2X, V2V, 5G & Connected Vehicle Technologies

Sensor Fusion, Sensor & Perception Technologies, Imaging Systems, Radars & Computer Vision

• Embedded Computer Vision for ADAS & Automated Driving
• Testing, Simulation & Calibration of Sensors & Importance of Disengagements, Integrity, Robustness & Security
• Achieving Incredible/Sufficient Level of Perception & Prediction Accuracy in Sensor Suites for Urban & Highway Driving Speeds
• Mass Deployment of Sensor Suites & Entering Mass Production for L4+ Autonomous Vehicles
• Value & Cost Optimization of Sensor Sets with Compromising Safety
  Application of Deep Learning in Sensor Fusion, Data Fusion & Role of Radar Sensors
• High-resolution maps offering context information for scene understanding

Safety & Security: Active Safety, Functional Safety, Operational Safety & Safety-Critical Systems, Embedded Systems & Cybersecurity

• ISO 26262 & Functional Safety in Autonomous Vehicles
• SOTIF & achieving functional safety for deep learning algorithms
• Ensuring functional safety with AI and machine learning
• Humans in Charge of Autonomous Testing Situations & Safety Testing on the Road
• Scaling embedded development teams & integrating systems with mixed protocols and interoperability before hardware exists