Overview

Enable safe, user-centric, and efficient mobility through cooperative intelligence and control across users, vehicles, and infrastructure

Human Factors and Interaction

We study how human users perceive, understand, and respond to intelligent mobility systems. Our research focuses on driver behavior, situation awareness, cognitive workload, user responses to automated systems, human-vehicle interaction, trust and acceptance of automation, and interface design for safe and intuitive mobility.

Vehicle Intelligence and Control

We develop intelligent vehicle systems that connect onboard perception and vehicle-centric vehicle-to-everything (V2X) communication with prediction, decision-making, planning, and control for safe, energy-efficient, and user-centric mobility. Our research focuses on vehicle dynamics and powertrain modeling, multi-modal sensing and sensor fusion, connected-vehicle communication, motion and traffic prediction, trajectory and motion planning, Advanced Driver Assistance Systems (ADAS) and automated driving systems, and integrated powertrain- and vehicle-level control.

Infrastructure Intelligence and Network Control

We develop intelligent infrastructure systems that integrate information from connected vehicles, roadside sensors, and transportation networks to understand, predict, and manage mobility at corridor and network scales. Our research focuses on infrastructure-centric data integration, regional traffic state prediction, queue and congestion prediction, and demand-supply management through traffic signal control, route guidance, and network-level coordination.

Verification, Validation, and Real-World Testing

We establish systematic workflows for translating virtual mobility scenarios into controlled experiments and real-world evaluation. Our research focuses on scenario generation and calibration, multi-scale simulation, X-in-the-loop(XIL)-based validation, scaled automated vehicle experiments, track testing, and public road deployment.

Cross-Cutting Integration

Across these four research areas, we integrate human users, vehicles, infrastructure, and validation into a unified framework for cooperative mobility. By combining established theories, physics-based models, control methodologies, and emerging AI techniques, we aim to extend the capabilities of today’s mobility solutions while pioneering next-generation systems that are more adaptive, scalable, and intelligent.