We develop methods for reliable and safe learning-based intelligent systems, addressing provable safety, safety under distribution shifts and uncertainty, and broader AI safety challenges.

We develop collaborative intelligence platforms, or operation centers, that integrate information from distributed and heterogeneous sensors, and provide coordinated guidance to diverse autonomous agents for safer and more efficient operation.

Smart city testbed

The Smart City Project utilizes a scaled-down map of real-world intersections at a 1:15 ratio. Consequently, vehicles, infrastructure, and other structures are also reduced to a 1:15 scale, and we refer to this as a "semi-realistic" testbed. This feature distinguishes it from simulations by incorporating realistic sensors, communication, and control noise, providing a more realistic data collection and physical movement experience. Furthermore, the infrastructure, such as traffic lights, is considered "intelligent" with sensors and computing modules. Unlike devices designed for passive control of current traffic flow, this "intelligent" infrastructure actively uses continuous information sharing with vehicles through V2X technology. This approach is pivotal in future technology development, enabling active traffic flow control and cooperative perception.