Traffic congestion is a challenge that faces transportation in urban cities worldwide. Congestion due to intersections is one of the top four reasons for traffic jams. It causes an increase in pollution and fuel consumption, in addition to a decrease in road mobility and utilization. Intelligent Transportation Systems (ITS) and Autonomous vehicles(AVs) provide intelligent approaches to solve traffic congestion. In this study, a performance-based comparison is implemented between an existing centralized intersection controller and a suggested novel decentralized intersection controller, that uses the Artificial Potential Field (APF) concept. An adaptive fuzzy-PID controller is introduced to the centralized intersection management system, then compared to other controllers from the literature and the suggested decentralized controller. Both approaches are compared in terms of performance metrics including average intersection throughput, average delay time (ADT), and maximum delay time (MDT). Both approaches are verified using a developed simulation environment using MATLAB/SIMULINK. The proposed decentralized control system showed better results than that of the centralized control system on the aspects of average throughput, Average and Maximum Delay time (MDT).