This paper proposes a new intelligent traffic control (ITC) system which is more efficient than the traffic control system currently used in the state of Kuwait. The proposed ITC system is designed as a dynamic system by using a fuzzy expert system; the fuzzy rules are applied in the visual basic and computer-based program (Excel) to run the validation process. The developed control system applied on five intersections in the grid network at four periods. The results show that the number of vehicles passing the intersection phases is increased in most phases by an average of 12.9% at the first period, 23.3% at the second period, 10.4% at the third period and by 21.2% at the fourth period. For the same periods, the phases green time is increased by an average of 9.1%, 5.8%, 9.9% and 6.3%. And the number of intersection cycles remains constant at the most time which means that the developed control system distributes the phases green time dynamically based on the traffic situation.

The problem of traffic delay and congestion is a severe problem in the world due to the population growth and difficulties in changing the infrastructure. This issue is being studied by researchers and international traffic centers because the traffic problem affected by the delay in services and products and the negative economic that traffic problem causes. It is difficult to improve the traffic system performance by using the traditional control methods. Many studies had been conducted using the fuzzy logic system and neural network to control the road intersections. In this article, the artificial intelligence traffic control principles and approaches which applied in the traffic signal control are reviewed. A comparison between the artificial intelligent systems and some points of view about future research in this area are proposed. The review shows that the traffic performance of the fuzzy controller has better performance than traditional traffic signal controls, especially during heavy and uneven traffic volume conditions.

An adaptive control system is developed using a fuzzy method to improve the traffic control system performance and to reduce the overall delay for four phases simple intersections within a grid of network. The main functions of the developed control system are to accelerate the cycle time and to reduce the loss time by determining the green time for each phase based on traffic flow. The fuzzy rules are employed using visual basic and computer-based program (Excel) to run the validation process. The developed control system is tested on five intersections in a simulated network in the State of Kuwait during four different peak periods. The results indicated that the number of vehicles passing through intersection phases has increased in most phases by an average of 12.9%, 23.3%, 10.4% and by 21.2%. The green time is increased by an average of 9.1%, 5.8%, 9.9% and 6.3%. Number of intersections' cycles remain constant at most of the time which means that the developed control system distributes the green phases' times based on the traffic situation. The developed control system can be applied on simple intersections with four perpendicular phases that consist of collector, major arterial or minor arterial roads.