Using mobile phone data to solve the traffic problem is an important application of social computing. In this paper, we used large-scale mobile phone data to estimate dynamical traffic demand and modeled the Internet of Vehicles information network, thus simulating the vehicle’s spatial distribution and the information transport efficiency. First, we studied the largest vehicle cluster and the information transport efficiency of Internet of Vehicles under different vehicle-vehicle commuting distance and internet of vehicles’ using rate. Next, we proposed a bipartite network to analyze the strategy of building information transit towers. Finally, we studied the mechanisms of how vehicle-vehicle commuting distance, Internet of vehicles’ using rate and information transit tower influence internet of vehicles’ coverage and information transport efficiency. We believe that our work can provide useful information for future development of Internet of vehicle.