Algorithm And Simulation Of Signal Control Based On City Highway Intersection

With the rapid development of economic, transportation has become more and more important for modern economic life. Currently, Traditional traffic control system obviously couldn’t meet the current transport requirement in cities. Considering the complexity of urban traffic and the limitation of traditional traffic control method, the thesis applies the fuzzy control theory and genetic algorithm to the research area of intersection signal control in order to shorten the queue length in intersection as short as possible. Therefore, it will be significantly necessary for the development of intelligent transport control to study optimizing timing plan.Base on the study of city traffic signal control theory, After the status analysis of correlational research on urban traffic controls both in domestic and overseas field, it is aware that the single intersection theoretical studies have been relatively perfect. But it is unsatisfied for the effect of enhancing traffic capacity of the whole traffic network by using control of single intersection. Therefore, research on signal coordinate control at main road intersections acts as the fundamental method of solving urban traffic problem. Based on a single intersection of four phases, the thesis mainly focuses on this research in depth.The thesis, taking four-phase traffic signal control in single intersection as an object of study, aims at designing a fuzzy control scheme. Through stimulation, compared with timing control and inductive control, the fuzzy control scheme has been proved to be better than traditional traffic control method. Then, the thesis analyses their individual traits of traditional FC algorithm and classic two-stage FC algorithm, thus improving their shortness. Arterial multiple intersections based on four-phase traffic signal control is mainly studied, especially arterial cooperative fuzzy control system. Two-stage modified FC algorithm is applied to control the green light delay in phases and phase switching. Simulation experiment showed that the method is able to shorten the length of queues. Because artificial designed membership function of fuzzy controller is not always fit. The thesis adopts adaptive genetic algorithm to optimize membership function of FC on the basis of past data and experience record, making the fuzzy membership function adapt to alteration in different traffic conditions. Compared with previous fuzzy controller after simulation experiment, it is proved that adaptive genetic algorithm is more reasonable. At last, through VISSIM, it is tested definitely that the optimized two-stage modified fuzzy control is more effective on cutting down queue length at intersection.