The technologies of traffic information collection using floating car equipped GPS have been become one of the main important means for real-time collecting traffic information in intelligent transportation system. The intervals of traditional traffic information collection technologies using floating car equipped GPS are simplex and equivalent at present. The sampling interval cannot be obtained according to geometric condition of load network and diversity of traffic status. Aiming at the ineffectiveness of the existing sampling interval algorithms, a real road network oriented optimization method of floating car sampling interval is proposed. Firstly, the urban road network is divided via quad-tree model. Thereby, the spatial sampling resolution can be acquired; Secondly, the short-term speeds of floating car are predicted according to the history track; Finally, the optimal sampling intervals are obtained, simultaneously, the spatial sampling resolution cannot be influenced. The results of simulation and experiment show that the sampling interval can be dynamically determined under the circumstances of different complexities of road network. The sampling result can notonly ensure sampling data precision, but also reduce data capacity.