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Team#28806 Page 1 of 24 Freeway traffic simulation model Abstract The ultimate goal of the entire modeling process is to analyze the performance of the keep-right rules in the light and heavy traffic. First of all, on the basis of cellular automata model, we establish the two-lane cellular automata model and three-lane cellular automata model to simulate the freeway traffic and analyze the performance of the rule according to the flow rate, speed, density and safety. The results are: In light traffic, density is less than the critical density. The vehicles reach at maximum average speed. There is a positive linear relationship between flow rate and density while average speed is constant; in heavy traffic, density is greater than the critical density. With the increase of density, road congestion occurs, and the average flow rate and average speed decrease; when safety probability increases, the maximum flow rate and average speed decrease. For further study, we use VISSIM5.20 to simulate the traffic. The analysis indicates that with the increase of the traffic flow, the lane changing behavior first increases and then decreases. When the safety decreases the lane changing behavior increases. Comparing with the Symmetric two-lane cellular automata, this rule is not effective in promoting traffic flow. We promote the fast-slow model to improve traffic flow. Additionally, referring to relevant data, we conclude that because of the different Coriolis Effect in north and south hemispheres, vehicles keep right are more safe in north hemisphere while in the south hemisphere are better to keep left. Then we introduce the Intelligent Transportation Systems (ITS) to establish the ITS cellular automata model (ITS CA). By comparison, the ITS CA has a significant effect on improv