Regional Traffic Control Analysis And Research

At present, with the rapid economic development, accelerating the urbanization process, the number of vehicles maintains rapid growth in traffic. Therefore traffic problems as the important bottleneck seriously constrain urban development and quality of life for residents. The face of rapid increases in vehicle traffic volume and limited resources, how to relieve a wide range of traffic congestion, improve road network capacity, reduce the number of traffic incidents to avoid the waste of valuable resources into Urban Road Network Management urgently needs to be resolved problem. Regional Traffic Control as Intelligent Transportation System key technology, as it can significantly alleviate these traffic problems, with the social significance and economic value, will be the next hot field of intelligent transportation and key.In this paper, in order to achieve effective to ease traffic flow for the purpose of information in a wide range of reading, the intersection of the regional road network in this study, based on the following aspects of the work done in-depth study:(1)Summarize the current status of research in the field of traffic control, including the intersection traffic control research and development, Route Traffic Control research and development, regional traffic control research and development. Particularly on Intelligent Computing in research and development of traffic control were introduced, the commonly used methods of computational intelligence: fuzzy control, evolutionary computation, neural networks are described in the application of traffic sector Research. At the same time as the necessary preparations for the follow-up section, an overview is given about traffic control important parameters and concepts in the process of traffic control.(2)To a typical single-intersection region as the control object, construct a single intersection discrete traffic model. In this model, the release of vehicle traffic and vehicles enter the constant arrival rate to queue length for the system state variables, through program design and implementation of traffic modeling, using small step test method optimized green time, reduce the queuing length, thereby validate the model simulation of the effectiveness of intersection conditions.(3)for a fixed phase isolated intersection traffic flow control problem, including phase change proposed fuzzy controller and fuzzy controller for two-stage fuzzy control method, in which the phase transformation of fuzzy controller to judge the phase transition, delay fuzzy controller determine the delay of the green time, the text on the two fuzzy controller to achieve given the design process, the simulation compared with the sensor control obtained, this method achieved the green light to shorten the delay time, reduce delays, make access more the purpose of smooth, but the adaptation effect of saturation by the traffic situation.(4)Considering multi-junction area traffic control complex, stochastic, discrete strong interference characteristics of many factors, the multi-agent control structure of the region is proposed based on multi-agent technology built of loosely coupled relationship and their control structure design of Intersection-level multi-agent, control structure design of regional multi-agent, structure design of the center control multi-agent are given a detailed description. In particular the simulation process to a regional multi-agent controller on the intersection traffic unit as the research scope, focus on the two junctions in the traffic jam situation of appears to coordinate the solution process. When the regional level agent faces intersection level agent coordination request, the genetic algorithm is used an important tool to optimize control parameters to achieve the overall regional traffic flow optimization. The results show that under the same conditions, compared with the traditional timing control, the index performance is greatly improved and this method is effective and feasible.