| According to the recent research on intelligent traffic control system at home and aboard, this dissertation lays a strong emphasis on the study of the traffic signal's global optimization control. Depending on getting the crossway transportation data, the intention of the study is to make use of the expert system, neural network and genetic algorithm to analyze the dynamic characteristic of transportation and to form the global optimization control order, and to realize the local signal lamp control by the method of utilization fuzzy control. A sort of project of an urban traffic signal control system is presented in the dissertation based on the weakness of intelligent traffic control system. A traffic signal control method using fuzzy logic controller in urban road intersection is proposed in the project, which uses current phase and next phase vehicles waiting queue to determine each phase time. And FN-BP algorithm is presented in allusion to fuzzy neural network in the dissertation, which improves the constringency speed and precision of the conventional BP algorithm. The dissertation also lays the emphasis on studying an intelligent transportation method to fuzzy neural network base on genetic algorithm, which can realize traffic signal optimization. According to the object-oriented software development concept and under the direction of the before-mentioned algorithm, Signal - Urban Traffic Control System is realized by VC++, which approves the rationality of system design and the validity of realization for getting the reasonable statistical result. As pointed out by the experimented results, this algorithm is more efficient than the conventional BP algorithm on the aspects of convergence performance and the ability of function approximation. Better control parameter of the highly robust capability can be found, which uses global optimization control based on the genetic algorithm under the dynamic transportation circumstances, and realizes the zone control globally. |
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