People



Prof. Francesco Borrelli
’s group at UCB focuses on the theoretical and real-time implementation issues of Model Predictive Control. In the past, we have worked on applying predictive control strategies to automotive active safety, specifically for lateral stability control and obstacle avoidance on slippery snow-covered roads. Our group focuses on the integrated control framework for the automotive CPS that accounts for driver and environment uncertainties in the control design process.


Graduate Students




Prof. Karl Hedrick’s Vehicle Dynamics and Control laboratory at UCB focuses on applying advanced nonlinear control strategies to a variety of problems including intelligent vehicles, engine cold start control, and human agent task allocation. Currently, we are interested in studying the vehicle model parameter uncertainty and the vehicle-environment interaction.


Graduate Students







Prof. Ruzena Bajcsy is the director of the Teleimmersion laboratory at UCB specializing in 3D stereo reconstruction, motion capturing and human movement analysis. In the past, we have used marker-based motion capture systems to study driver behavior. We are currently working on using vision-based in-vehicle sensors and inertial measurements with tools from machine learning to predict driver behavior.


Graduate Students






Prof. Edgar Lobaton’s Active Robotic Sensing laboratory at NCSU focuses on the design of robust techniques for estimation from imaging data, and control of robotic platforms under uncertainty and minimal sensing. Our current research focuses on vision algorithms in which robust feature matching is used to construct 3D models of the environment that lead to safe semiautonomous driving.


Graduate Students
Chunpeng Wei






Prof. Ed Vul’s laboratory on Cognition and Inference in the Department of Psychology at UCSD works at the intersection between the computational and algorithmic descriptions of human cognition, to reconcile models of human behavior as statistically optimal computations with the findings of cognitive psychology. Our current work is aimed at developing a model of human driving behavior based on approximate (sample-based) inference of optimal stochastic control.


Graduate Students