Intelligent Vehicle & Mobility Validation Framework

As intelligent vehicle and mobility systems become increasingly complex, developing them requires an integrated research framework that connects data collection and generation, simulation, algorithm development, and real-world validation within a single loop. X-in-the-Loop (XIL) methodologies sit at the center of such a framework, since they allow vehicle perception and control algorithms to be validated systematically, repeatably, safely across diverse operating conditions and development stages.

This project develops a unified data-simulation-validation framework for intelligent vehicle and mobility control research at KAIST. Vehicle-infrastructure cooperative perception and control serves as the representative use case, through which the framework is tested for feasibility and scalability. Validation runs on both small-scale vehicle platforms and full scale vehicles in real-world environments, so that an algorithm can move from simulation to a real road without leaving the framework. The aim is to close the gap between simulation-based development and real-world deployment, and to make research on future intelligent mobility systems both reliable and efficient.