Intersection Signal Control Based On Fuzzy Logic

As China continues to accelerate the pace of urbanization and socio-economic development, while a substantial increase in the urban population. The number of vehicles has substantial growth, the balance between the needs of urban transport and transport infrastructure were broken. Traffic congestion is worsening, and the trend spreads from the front line and large cities to the second and third tier cities in the trend. New transport infrastructure cannot solve the contradiction between supply and demand, but also to enhance the capacity of existing transport infrastructure. So it is important to improve the level of traffic control and management, ease traffic congestion and the corresponding economic losses.Traditional traffic signal control us strict mathematical model, which cannot match the randomness and uncertainty of urban transport. We consider the introduction of artificial intelligence technology to optimize the signal control, with its good nonlinear approximation ability, good simulation of the human brain logic and stability and other advantages, only in this way can we improve the service level of intersection.Based on the understanding of the current traffic signal control development and basic theory, fuzzy control theory is introduced in, to overcome the defect of the traditional control method based on mathematical model. Do something to the traditional fuzzy control for further improvements to adapt to the new dynamic traffic signals control methods, and through MATLAB simulation, compared with timing control, the traditional fuzzy control, and validation methods. And further deepen the study for at Phase Sequence fuzzy control deficiencies exist, the use of particle swarm optimization parameters further and further reduce the average vehicle delay intersections, and the effectiveness of programming through MATLAB simulation methods.Finally, verify that the advanced nature of this method through the practical application of the case, and strike the optimal membership functions and fuzzy rules of the controllers against the case intersection, and the article provide an idea for the application of fuzzy logic in traffic signal control.