Urban Interrelated Intersections Study via Fuzzy Graph Theory

Such factors as geographical location and traffic volumes affect the interrelated degree of urban inter sections(IDUIs). For those traffic nets with fewer or no traffic data collecting devices, this paper studied its IDUIs with fuzzy graph theory, then got different control subareas. It first presented fuzzy graph theory, then concluded a kind of fuzzy logic algorithm on analyzing IDUIs and defined Cross Significance Coefficient(CSC)&Link Significance Coefficient(LSC)algorithm, last, a simulation example was carried out to verify its feasibility. In general, average traffic stop is decreased by 7.51 percent, average traffic delay is decreased by 11.76 percent, and average speed was increased by 14.26 percent.