Sub-area Division Method With Signal Control Method Optimization For Urban Area Traffic Control

Traffic signal control technology is a cutting-edge issues in the field of transportation management which has a wide application value in the area of vehicle management, traffic monitoring, intelligent transportation and so on. In recent years, with the rapid development of computer technology, through the creation and conduct of the research work of national research staff, many new control theory and control algorithms emerged one after another, and many have turned into sophisticated traffic control software and is widely used in practical engineering. However, due to the complex and changeable urban traffic environment and the huge amount of urban transportation system data and other factors, there are many imperfections and problems on traffic signal control technology both in theory and application, thus an excellent method of zoning and fuzzy control method has a certain academic and practical value. In this paper, based on the regional traffic control method, the research focused on the traffic division of the sub-region and fuzzy control of single intersection respectively.1)In allusion to the incompact division and coordinate method of traffic control sub-district division which lead to poor optimization effect on vehicle delay in a sub-region, thus acoordinated approach rating calculation method was proposed,and put forward different coordination process according to the difference in the degree of correlation; Calculations of network connection is based on Synchro coordinate factor and coordinate factor mainly calculate travel time, distance, flow, team form, cycle length and other factors; The coordination factor weights between two intersections was analyzed, the efficiency that caused by different coordinate method was simulated by software. So the proper proportions between method and efficiency were determined and it will reduce the delay of an area.2)Dealing with the problem of slow evolution that happens to high fitness individualsin the initial operation of conventional genetic optimized fuzzy controller, and low operation efficiency, the genetic algorithm optimization and fuzzy controllerwere studied respectively. Through increasing the crossover and mutation probability of high fitness individuals, the hysteresis phenomenon was reduced and the algorithm efficiency was enhanced; In the selection process of the population, the population size was moderately chosen, so that the search efficiency was improved; By using Gaussian membership function, the control characteristic is more gentle, and the effect was improved.