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Firstly, this paper analyzes the defaults of traffic model applying in campus road in China, such as lacking simulation of vehicles, pedestrians and bicycles under mixed traffic flow. Secondly, the paper proposes an improved multi-value cellular automata model for revealing complex traffic phenomena of pedestrian-bicycle, pedestrian-vehicle and bicycle-vehicle mixed traffic flow. The model includes different forward rules and drift rules for different traffic types under campus roads. Thirdly, considering the mutual interference among different traffic types, it is named different interaction behavior. Finally, the difference of the degree of interaction interference among different traffic types is simulated and analyzed. Through qualitative analysis on traffic fundamental diagram, the complex mixed traffic flow phenomena is simulated by this model successfully, such as overtaking, drift, interaction, free flow, synchronized flow, congestion flow, slow traffic on the right side, etc. Therefore, this research is not only have a profound theoretical and practical value for campus security, but also have the function of reference and guidance for urban mixed traffic network.

An improved multi-value cellular automata model for mixed bicycle traffic flow on campus