Due to the fact that the vehicle nodes rapidly move in the Internet of Vehicles and the topology of the Internet of Vehicles is highly dynamically changed, the Internet of Vehicles is prone to data aggregation, delay and the like, and great challenges are brought to the network communication and stability of the Internet of Vehicles to a great extent. However, a good Internet of Vehicles routing strategy not only needs to keep the rapid connection of the network, but also needs to keep the stability of the network, namely, the accessibility of the network is ensured. Therefore, the analysis and understanding of the accessibility in the Internet of Vehicles community are an urgent problem to be solved. The invention aims to solve the problems, In order to detect the communication inside theInternet of Vehicles community and keep stable, the accessibility method in the Internet of Vehicles community is provided; According to the method, a learning automaton theory is utilized, corresponding excitation functions and penalty functions are set through information exchange and competition deployed among community nodes, forwarding probabilities of different routes are adjusted in a self-adaptive mode, the Nash equilibrium state is achieved, and therefore the purposes of optimizing data transmission in the network on the whole and improving the accessibility of the Internet of Vehicles network are achieved.