| The development of science of society not only changed the situation of people’s daily life, but also educated them to enjoy convenient lives. So that, transportation as an important part of people’s daily life, gained more and more attention. Just as in big cities, smaller cities also have been interrupted by the problem of congestion. As a result, how to make the transportation flow fluently, even under the congestions, has become a significant issue in today’s intelligent transportation systems research.Successfully control the transportation lights can efficiently help dredging of traffic flow, which can make the flow fluent. The same time, public traffic, owning advantages such as bigger amount of passenger capacity, less pollution and resource usage, has been the most usual used method for residents’gong out. So, this article will start from the affection of traffic lights and the signification of public traffic lights (especially buses), try to find a method to combine the advantages of these two part.PSO algorithm has the disadvantages:easy to implement, excellent convergence and less parameters. So, this article will use the PSO algorithm to train the fuzzy definition algorithm, so that decide how to control the traffic lights. Particularly, this article will use the cooperative random PSO algorithm to enhance the function of PSO algorithm from two parts:maintain the diversity of the swarm by using other swarms’best history information to update velocities and positions, and keep the convergence speed of the algorithm by employing more useful information during the iteration.Article will present the results of the simulations; also compare the results of basic control method, fuzzy definition algorithm control and fuzzy definition algorithm using the PSO algorithm training.To gain the most amount of passenger passed, system will show the better performance of using the collaborative random PSO algorithm, and the traffic light control system based on buses priority. |
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