In the field of autonomous driving, safety is of utmost importance. In this study, we propose using dense reinforcement learning for safety validation of autonomous vehicles. Our approach allows for real-time assessment of safety and can be integrated into existing autonomous systems. By leveraging deep learning and reinforcement learning techniques, we can ensure that autonomous vehicles are safe and reliable on the road.