Deep reinforcement learning combines deep learning and reinforcement learning algorithms which are the subclass of machine learning algorithms. It maximizes the learning capability and adaptively controls various operations like traffic signals in VANETs. Applying deep reinforcement learning in traffic engineering is critical due to numerous signalized intersections, high dynamic environments, uneven vehicle distribution, and continuous action spaces.