Abstract—This paper presents a fuzzy traffic controller for controlling a multilane-multiple traffic intersection in urban city environment. The developed controller applied to the model is based on the cooperation and distributed mechanisms with the neighbors’ intersection. The phase sequence and phase length extension are used in decision making to provide efficient and more optimal traffic control. The input variables are normalized and the proposed fuzzy traffic controller is suitable to be used to any case study without modification to the controller modules. The simulation illustrates that the fuzzy traffic controller proposed in this study show a remarkable improvement over the existing fuzzy traffic controller without input normalization. I. INTRODUCTION RAFFIC control in urban networks is a nonlinear process varying dynamic characteristics throughout the day. The fundamental principle of urban traffic control is to respond to dynamic changes of the traffic demand and synchronizing traffic signal with the neighbor intersections. As the junctions in a road network are interconnected, the decisions made at one junction inevitably affect those made at the adjacent junctions. In multilane-multiple intersection, the traffic signal control operates dependently to neighbor intersection. This means that the control algorithm can be much complicated than algorithms for isolated intersection. The system controlling the intersection has a lowest degree of freedom to choose a control strategy for multilane-multiple intersection. In this case, a control strategy is choosing must be considering the traffic from upstream intersection and congestion occur in the downstream intersection. Traffic control system is nonlinear, fuzzy and nondeterministic, and traditional methods of modeling and control can’t work very well. As a perfect urban area traffic signals control system, it is supposed to respond to traffic demand and online- Manuscript received April 15, 2009. This work was supported in part by the Universiti Putra Malaysia and CAIRO, Universiti Teknologi Malaysia. Azura Che Soh, is currently doing PhD in Centre for Artificial Intelligence and Robotics (CAIRO) of Universiti Teknologi Malaysia, Jalan Semarak, 54100 Kuala Lumpur.(e-mail:azura@eng.upm.edu.my). Marzuki Khalid, is a professor and Deputy Vice Chancellor (Research & Innovation) of Universiti Teknologi Malaysia, Skudai, Johor. (e-mail:marzuki@utmkl.utm.my). Mohammad Hamiruce Marhaban is an associate professor with the Department of Electrical and Electronics Engineering, Universiti Putra Malaysia,43400, Serdang, Selangor.(e-mail:hamiruce@eng.upm.edu.my). Rubiyah Yusuf, is a professor and director of CAIRO, Universiti Teknologi Malaysia, Jalan Semarak, 54100 Kuala Lumpur. (e-mail:rubiyah@utmkl.utm.my). optimize timing plans in time, and then implement real-time control. Thus, the traffic system must have adaptive characteristic and automatic control strategy. Fuzzy controllers have proven effective in controlling a single traffic intersection [1]-[3], even when the intersection is somewhat complex. In certain instances, however, even if local controllers perform well, there is clearly no guarantee that they will continue to do so when the intersections are coupled with irregular traffic flow. Research on controlling a set of traffic intersections can be found in [4]-[6]. Jee-Hyong et. al. [4] applied the fuzzy logic approach for dynamic multiple traffic intersection in urban areas. The controller changes not only the phase lengths but also the phase sequences adaptively based on the traffic situation. References [5] and [6] were based on the distributed fuzzy controller which is adaptive to the traffic conditions. However, they dealt with simple traffic conditions, such as, regularly located intersections. They did not change the sequence of phases in their research. Changing of the phases sequence may confuse drivers, but in the view point of the performance of traffic controllers, it is much sought. If the sequence of phases is fixed and traffic conditions are often changed, the traffic signal cannot effectively deal with the traffic conditions which may result in deterioration of the of the traffic controllers. In the case above [4]-[6], the controller could easily handle changes in traffic flow, but required different parameter settings for each junction. The fuzzy membership functions of the input fuzzy variables of the controller are different for each lane depending on the lengths of the traffic. The ratio value for this input is required as the length of the lane is different. Using the ratio value not only decreases the complexity of the fuzzy logic system but also improves computation time. This paper presents the development of intelligent traffic light system based on the fuzzy logic approach applied to multiple-multilane intersection in an urban area. The controller is developed based on the cooperation mechanism and synchronizing mechanism with the neighboring intersections. The phase sequence and phase length extension are used in the decision making of the fuzzy controller. In this controller, the modification of input variables in the ratio values was purposely done to include all the related variables to one specific variable. Improving Fuzzy Traffic Controller for Multilane-Multiple Intersection Azura Che Soh, Marzuki Khalid, Mohammad Hamiruce Marhaban, Rubiyah Yusuf, Member, IEEE T 2009 IEEE International Conference on Control and Automation Christchurch, New Zealand, December 9-11, 2009 FrMT5.2 978-1-4244-4707-7/09/$25.00 ©2009 IEEE 1819