Motion planning and control for autonomous vehicles

• Longitudinal motion planning (speed planning) for enhancing ride comfort using Model Predictive Control (MPC) and Deep Reinforcement Learning (DRL)

• Longitudinal speed tracking control considering unknown disturbance using neural network-based adaptive control

• Lateral motion planning (path planning) for large vehicles on narrow roads

• Lateral motion control (path tracking) for large vehicles considering localization uncertainty

• Fully autonomous driving algorithms on actual urban roads

State estimation and connected driving with infrastructure

• Vehicle state estimation, including vehicle's mass, yaw-rate, and sideslip angle

• Map matching-based localization using extended Kalman filter

• Motion planning at intersections using Vehicle-to-Vehicle (V2V and Vehicle-to-Infrastructure (V2I) communications

Dynamics analysis, reverse engineering, and simulator development using hydraulic and pneumatic system and multi-body system analysis

• Development of dynamic simulation models and control algorithms for underwater vehicles and defense equipment