Simulink Controls a Vehicle in VR Environment with Reinforcement Learning Implementation

Simulink controls a vehicle in a VR environment equipped with 5 distance sensors. The vehicle gradually learns to avoid walls and obstacles using Q-learning reinforcement learning algorithm with neural network-based Q-function approximation. Implementation includes simulated annealing for exploration strategy, resulting in initial frequent collisions during training phase that significantly reduce after approximately 10 learning iterations. The 3D vehicle model utilizes the VR model originally published by "w198406141" in the virtual reality section of this forum, with integration through Simulink 3D Animation toolbox and custom S-function blocks for sensor data processing and control logic.