AI Summary & Key Takeaways
AI InsightResults show that the fuzzy controller can effectively minimize total delay and it is superior to compared methods.
📌 3 Key Takeaways
Abstract
The traffic problem is a multidimensional problem and traffic lights are the key points to solving this problem. Thus, optimum green light duration helps reduce the traffic congestion. “Queue length during red light” and “remaining vehicles in line after green light” are important parameters for the determination of the green light duration. In this paper, a single intersection is taken into account with mentioned two inputs of fuzzy logic controller considering each intersection approach one by one. The output variables are chosen as “phase selection” and “extend of green light duration”. Unlike many other studies, these output variables are combined into one system based on modal distinction. Each approach is normalized according to the number of lanes to calculate a membership function value: because of different capacities of intersection approaches. The model is solved using MATLAB fuzzy inference system. The delay parameter is considered as performance measurement. Accordingly, proposed model is compared with various traditional models in literature. Finally, the model is evaluated using ANN (artificial neural network modeling) and ANFIS (adaptive neuro-fuzzy inference system) and then the consistency of the results is checked. Results show that the fuzzy controller can effectively minimize total delay and it is superior to compared methods.