This study presents the development of a scaled-model-based Vehicle-in-the-Loop Simulation (VILS) environment for safe and cost-effective validation of autonomous driving control algorithms for large articulated buses and BRT vehicles. The system integrates an indoor positioning module based on the HTC VIVE Tracker, a controller implemented on ROS2, and a Redis-based communication architecture to enable real-time data interaction. An Extended Kalman Filter (EKF) was applied to integrate IMU and positioning data, enabling precise estimation of vehicle velocity and yaw rate. Evaluation of communication latency and positioning precision confirmed performance within 1 cm under scale-restored conditions, demonstrating sufficient capability for autonomous driving validation. Experimental results verified the integrated operation of the controller, sensors, and communication modules. The proposed VILS environment was shown to reduce the risks and costs associated with full-scale vehicle testing while providing a repeatable platform for autonomous driving control validation.
Park et al. (Thu,) studied this question.