The Reinforcement Learning (RL) algorithms assist VANETs to maximize the routing efficiency. The RL is a subtype of a machine learning algorithm that works based on the past behaviors of nodes and enables optimal solutions for future behaviors. The RL algorithms also improve the quality of service of VANET routing protocols in terms of packet delivery ratio, end-to-end delay, bandwidth, control overhead, and throughput. The modest memory utilization and minimum computation complexity make the RL most significant than other learning techniques.