Geographic routing is a research hotspot of the internet of vehicle (IoV) and intelligent traffic system (ITS). In practice, the vehicle movement is not only affected by its characteristics and the relationship between vehicle and position, but also affected by implicit factor. Pointing to that problem, a routing algorithm based on vehicle position analysis (RAVP) is proposed which combining the vehicle motion position probability matrix, the vehicle position association matrix, and the implicit factor to study the influence of vehicle position potential features, Vehicle Association potential features and hidden factors on its performance, so as to obtain the vehicle moving trajectory. By normalizing vehicle distance and cache, the vehicle data forwarding capability is obtained and the transmission decision is established. Simulation results show that the proposed algorithm performs better than the other three routing algorithms in terms of packet delivery ratio, average end to end delay and routing overhead ratio