A traffic signal controller for an isolated intersection using fuzzy logic model

With the revolution of the new technologies and intelligent transportation systems (ITS) as one category of the artificial intelligent (AI) models, fuzzy logic models (FLMs) were considered as one of the promising methods applied in signalized intersections. In general, results show significant improvements on the efficiency of the traffic networks and intersections. This paper presents a new method of developing an optimal real-time traffic signal controller using the fuzzy logic technique/method (FLM), taking into consideration all various incoming traffic flows. The developed FLM was designed for an isolated intersection with four legs, split phasing, and three different movements (through, right, and left). This research aims at developing an FLM that replicate the control settings of optimized methods. Calibration and validation tests were conducted to ensure accuracy and efficiency of the developed model. Results show that the developed FLM outputs are close to those obtained from optimum methods for traffic signal control systems.