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Traffic has always been the infrastructure of national economic and social development. With the pace of urbanization unprecedented speedup and the increase of vehicle possessions, traffic congestion has become a big problem in modern cities. Regional traffic guidance system provides traffic information for road travelers in pre-trip and in on-trip, and guides travelers to change travel modes, choose travel routes, and save travel time to take full advantage of road network resources. Variable message sign (VMS) is one of the main ways to provide traffic information in metropolitan road network, but traditional VMS guidance regions are designated manually by traffic administrators to cause very bad effectiveness and efficiency, and there are even some VMS used only for advertising that have nothing to do with the traffic guidance management. We analyze the traffic guidance model based on VMS, and study the dynamic regional partition problem and the dynamic traffic guidance problem under real-time traffic conditions, and put forward the architecture and two algorithms. The architecture serves mainly for the whole cycle of developing VMS based guidance from raw data collection to traffic information publish. The algorithms dynamically partition traffic guidance regions and dynamically change the vehicle turning ratio at intersections to balance traffic flow and save travel time in guidance regions. The cellular automaton method based on SWARM platform is employed to simulate traffic environment, and verify the effectiveness and efficiency of the model and the algorithms by compare with the other traditional regional guidance algorithm.