With the increasing applications of new technologies such as smart driving, autonomous driving and Internet connectivity, traditional in-vehicle networks are difficult to meet the Quality of Service (QoS) demands of diverse applications. In order to improve the data transmission rate and guarantee the QoS demand of services in the in-vehicle network, a deep reinforcement learning QoS routing algorithm based on SDVN is designed in combination with Software-Defined Vehicular Network (SDVN) technology. The algorithm can realize intelligent control and optimized management of data transmission in the in-vehicle network to ensure the control, distribution and monitoring of in-vehicle network traffic and improve the quality and efficiency of in-vehicle data transmission. The experimental results show that the routing algorithm can better reduce the delay of the in-vehicle network and has better optimization performance compared to the traditional routing algorithm.