Perception-Driven ML: How to develop benchmarks for camera- and LIDAR-related perception?
Next-Generation Radar: How to include intelligent radars into AV sensor suits?
Camera Technology & Computer Vision Algorithms: How to turn cameras into primary sensors for object recognition and classification, localization, decision-making, trajectory planning, and vehicle control?
Open/Modular Verification & Validation: How to manage rapidly changing test requirements?
Sensor Fusion: How to properly weigh sensors at run-time?
Perception Stress Testing: How to automatically identify where perception is brittle using unlabelled data?
Vision Geometry & Deep Neural Networks: How to verify deep learning detection with vision geometric principles?
Reinforcement Learning for Vehicular Path Planning: How to make use of deep learning for AVs?
Full Stack Software Suites for AI: How to develop hardware-agnostic and scalable solutions?
Self-Supervised Learning for AVs: How to collect and label data at scale?
Data Processing & AI: How to develop software architectures and overcome hardware challenges?
Interpretable Learning for AVs: How to use visual explanations that causally influence CNN output?
Sensor Selection, Design & Innovation: Which are the latest technologies?
Weather & Vision Environments: How to ensure safety in unfamiliar and challenging weather environments?
The Software-Defined Car: What is the role of SDV in ADAS?