In this paper, to overcome the problem of increasing traffic, using state space equations, a comprehensive model of urban traffic network are obtained in a isolated intersection. Then, two fuzzy logic controllers, one for optimized green time of traffic lights and one green phase is used for an extended time.In this system, types of sensors is video detection, they are placed strategically at incoming and outgoing legs (lines) and the controller utilize the information received from these sensors to make optimal decisions to minimize the goal function. The simulation results show that TAOSF (Traffic Actuated Optimization Signal Fuzzy control) had a great improvement in 6 different traffic conditions such as certain, uncertain, using random data, and in 4 different traffic conditions using the real case study of OSTANDARI intersection in Mashhad, Iran, in comparison with the fixed time controller, real operation of Australian SCATS (Sydney Coordinated Adaptive Traffic System) system, TASFC (Traffic Actuated Signal Fuzzy Control) system in previous work for estimation of the goal function which is minimizing the queue length and the delay time of the vehicles.

Every day growth of the vehicles has become one of the biggest problems of urbanism especially in major cities. This can waste people's time, increase the fuel consumption, air pollution, and increase the density of cars and vehicles. To improve this problem, we first designed a comprehensive model of urban traffic network in this article, using state space equations and SIMULINK Program MATLAB and then by using a novel algorithm, two fuzzy controllers for controlling traffic light in a two phase isolated intersection in the multi Variable Control System.In this system, types of sensors is video detection, they are placed strategically at incoming and outgoing legs (lanes) and the controller utilize the information received from these sensors to make optimal decisions to minimize the goal function. The simulation results show that TASFC (Traffic Actuated Signal Fuzzy Control) had a great improvement in 6 different traffic conditions such as certain, uncertain, using random data, and in 3 different traffic conditions using the real case study of EBADI-KASHANI intersection in Mashhad, Iran, in comparison with the fixed time controller, real operation of Australian SCATS system and FSCS (Fuzzy Signal Control System) system in previous work for estimation of the goal function which is minimizing the queue length and the delay time of the vehicles.