My work lies in the learning, control, and design of autonomous systems with an emphasis on connected automated vehicles (CAVs). I have been committed to developing robust autonomous vehicles, augmented reality (AR) technology, and V2X systems at Mcity. The highlights include: (1) a robust self-driving algorithm/software stack enabling high-level CAVs; (2) a data-and-AI-driven sensor-level augmented reality (AR) system for efficient safe CAV tests. These systems have been deployed on the Mcity CAV fleet and Mcity testing track for daily operations. I am interested in using big naturalistic human-driving data to train motion planning and control algorithms of self-driving cars, so the automated cars could behave with better roadmanship and thus higher acceptance. I am also interested in data-driven low-uncertainty learning algorithms for object detection, tracking, and fusion, in order to build the perception system of safety-critical autonomous systems.
Gabor Orosz is an Associate Professor of Mechanical Engineering and Civil and Environmental Engineering. His theoretical research include dynamical systems, control, and reinforcement learning with particular interests in the roles of nonlinearities and time delays in such systems. In terms of applications he focuses on connected and automated vehicles, traffic flow, and biological networks. His research has been supported by the National Science Foundation and industrial funds. His recent work appeared in journals like IEEE Transactions on Automated Control, IEEE Transactions on Control Systems Technology, IEEE Transactions on Intelligent Transportation Systems, and Transportation Research Part C. For the latter journal he has also be serving as an Editor. WIRED magazine reported on his experimental results when his team built a connected automated vehicle and evaluated it in real traffic. He served as the program chair for the 12th IFAC Workshop on Time Delay Systems and served as the general chair for 3rd IAVSD Workshop on Dynamics of Road Vehicles, Connected and Automated Vehicles.