Research > Research topics

Vehicle Dynamics Modeling & Performance Analysis

This research focuses on advancing vehicle dynamics and control through the application of Physical AI, machine learning, and model-based control theory. By integrating data-driven algorithms with physical vehicle systems, we aim to enhance motion control performance, stability, and adaptability under various driving conditions.
The research further involves Hardware- and ECU-in-the-Loop simulations to validate real-time control strategies, bridging the gap between virtual intelligence and physical actuation for next-generation mobility systems.
  – Automotive dynamical actuating mechanism design
  – Active controlled systems design for vehicle dynamics
  – Vehicle Dynamics Control
  – Hardware/ECU-in-the-Loop Simulation based control system development and validation

Human-centric Vehicular Technology

This research aims to advance human-centered vehicular technology by leveraging Physical AI, machine learning, and big data analytics.
Through the integration of emotional and perceptual factors with vehicle control intelligence, we analyze physiological signals and driver behavior to develop adaptive motion control strategies.
These technologies enable vehicles to respond dynamically to individual comfort and emotional states, realizing an intuitive and empathetic driving experience.
– Objective evaluation methodology of emotional and perceptual factors
– Human-centered path planning and following algorithms
– Personalized driving control and adaptive comfort strategies

Future Mobility Platform Architecture

This research theme addresses the architecture of next-generation mobility systems integrating vehicle, infrastructure, and AI technologies.
We design scalable control frameworks and cooperative algorithms to enable seamless coordination among electric, connected, and autonomous mobility platforms of the future.
 – Analytical methods for system design requirements
 – Integrated mobility control system architecture design
 – Advanced driving and cooperative control algorithms