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Floating car data (FCD) is an important material for a broad range of application such as traffic management and control, traffic conditions computation. The traditional map-matching algorithms were more focused on the accuracy of the positioning on the road network than on the computational speed of the algorithms. This approach designs a structure of road network which divides the road network into two levels, and the idea of partitioning the road network into mesh is introduced. Using the information about the position and the direction of the vehicle traveling and the topological feature of the road network, a quick map-matching algorithm which is applicable to real-time handle large-scale FCD is proposed. Examples are provided on a large data set for the Beijing area. The paper demonstrates the efficiency of the algorithm in terms of accuracy and computational speed.