Intelligent Transportation Systems
The D²iCE Intelligent Transport Systems research domain covers many aspects of sensing and automation for driver assistance systems and self-driving cars. The domain area is led by Ciarán Eising, who spent more than 12 years working in industry developing sensing solutions for autonomous vehicles. Machine learning has already and promises to continue to meaningfully contribute to high-quality vehicle automation. We collaborate with many companies working in the automotive sensing space, ensuring our innovations have the best chance of making a real end-user impact.
RadNet - Automotive detection, tracking and prediction using radar data
Radar sensors works brilliantly in low light and adverse weather conditions, unlike other automotive sensor modalities. This project looks at using radar data for pedestrian detection, tracking and prediction to avoid road accidents.