Two-Stage Fuzzy Logic Controller for Signalized Intersection

Traffic efficiency is commonly regarded as the most important target for the control of signalized intersections. However, from the fairness point of view, it can be argued that all vehicles at a signalized intersection should have equal passing opportunities. In this correspondence paper, a two-stage fuzzy logic control model for an isolated signalized intersection has been proposed, where both traffic efficiency and fairness have been considered simultaneously. At the first stage, a green-phase selector has been developed to select the subsequent green phase. At the second stage, a green-time adjustor has been proposed to determine the green time for the selected phase. An offline genetic algorithm (GA) has been developed to optimize the fuzzy rules and membership functions of the two controllers. The simulation results demonstrate that the proposed model outperforms the vehicle-actuated control model and the model proposed by Pappis and Mamdani in 1977 in terms of both traffic efficiency and fairness. The performance of the proposed model can be further improved after its rules and membership functions are optimized by using GA.