The UT EcoCAR team has worked diligently towards re-engineering their 2019 Chevrolet Blazer during Year 3. The main focus for this year has been the integration of Connected and Automated Vehicle (CAVs) technology. The UTK CAVs subteam, overseen by CAVs Faculty Advisor Hairong Qi, has been integrating cameras and radar onto their vehicle.
Qi has guided the team through these activities by utilizing her experience and research on the evolution of computer vision. She is the director of UT’s Advanced Imaging and Collaborative Information Processing (AICIP) Lab, where her main area of research is computer vision and machine learning.
You may ask, how does Qi’s interest and expertise relate to EcoCAR? Autonomous driving vehicles are an example of a complex cyber-physical system. Perception and fusion of data collected from the onboard sensor suite of a vehicle is one key component that enables autonomous driving. During autonomous driving, systems identify and sort various objects by using cameras and sensors embedded within a vehicle. Computer vision then identifies these images and videos and assigns them a specific size, shape or color. Computer vision can then produce results for a driver in real-time.