Reduction of Delays at Isolated Signalized Intersection using Novel Golden Eagle-Based Fuzzy Signal Controller

Traffic signal management is an important concern in transportation. Traffic prediction is attained more interest in the last few years. With the rapid infrastructure revolution and the automobile industry, all countries face traffic congestion. The development of AI and the high dimensional dataset availability has attracted many scholars to develop various techniques to maximize the green time duration. Generally, traffic signal control (TSC) is utilized in real-time due to the lower establishment price. However, these approaches don't provide good function parameters, especially in unbalanced traffic. So artificial intelligence is utilized in traffic signal control to degrade the delay period. Inadequate traffic demand adoption and high training expenses are the disadvantages of the transportation. So, the novel Golden Eagle-based fuzzy signal controller (GEbFSC) is proposed in this article to reduce the travelling time, delay time, and queue length. The suggested methodology monitors and detects the traffic from the standard traffic flow dataset. By contrasting the effectiveness of the proposed model with existing methodologies, its validity is confirmed, and the improvement value is assessed. Finally, the comparative analysis confirms that the created technique outperformed other techniques.