Improvement of genetic algorithm and its application in optimization of fuzzy traffic control algorithm

For the complex and time-varying traffic flow, single-strategy based fuzzy traffic control algorithms are not very ideal. In order to further improve the capacity of isolated intersection, we propose a multistrategy fuzzy control algorithm to adapt to the variation of urban traffic flow, and then optimize its control rules and membership functions by using improved genetic algorithm. The simulation result shows that compared with traditional genetic algorithm, the efficiency of improved genetic algorithm is higher, and its performance is more stable. The multi-strategy fuzzy control model possesses the stronger self-adaptive competence and performance.