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The simulation video showcases two race cars in a 3D environment controlled using different algorithms: Model Predictive Control (MPC) and Linear Quadratic Regulator (LQR). The black car, using MPC, optimizes its path over a 1.75-second prediction horizon, adjusting its acceleration and steering every 0.2 seconds to minimize path deviation, while the white car, using LQR, computes control inputs to minimize a cost function penalizing deviations and control efforts. Both cars follow smooth reference paths visualized in yellow, with real-time debug lines indicating their positions. As the cars navigate the track, the black car’s trajectory is plotted in red lines, and the white car’s trajectory in blue lines, demonstrating smooth and precise path tracking. The simulation continues until each car reaches its goal within a 0.2-meter threshold, culminating in a plot that compares the tracking performance of both control strategies, illustrating the effectiveness of MPC and LQR in autonomous vehicle path following.