Digital Twin

The Digital Twin is a digital replica of the physical entity in the real world, which leverages big data and cloud/edge computing to benefit the mobility system consisting of human, vehicle, and traffic.

Foundation Models for Autonomous Driving

Large language and vision models (LLVMs) can help autonomous vehicles understand the underlying logics of human commands and traffic scenes to facilitate human-autonomy teaming.

Personalized Behavior Modeling

Personalized driver behavior (or more generally human factor) plays a crucial role in human-autonomy teaming, especially when the driver is operating Advanced Driver Assistance Systems (ADAS).

Human-In-The-Loop Simulation

Driving simulator allows human to drive vehicles modeled in a virtual environment, enabling comparison between proposed connected and automated vehicle technology with human driving behaviors.

Cooperative Ramp Merging

With advanced Vehicle-to-Everything (V2X) communication techniques, connected and automated vehicles can schedule their sequence and plan their speed trajectories ahead of time to avoid last-second speed change at the merging point.

Cooperative Eco-Driving

With advanced Vehicle-to-Infrastructure (V2I) communication technique, "cooperative eco-driving" provides real-time advices to drivers based on real-time traffic and infrastructure conditions.