Optimal control of signalized intersection using hierarchical fuzzy-real control

This paper presents a method based on precise modeling of traffic flow using a fuzzy-real algorithm for optimal control of a signalized intersection. By improving social indicators such as security, well-fare and economy, intercity transportation has increased and traffic congestion developed. Today, the plight of traffic congestion is the cause of waste of time, capital, and health risks. Although the construction of new streets, expressways, and highways can improve this situation, when inadequate space and limited budget is available, it is not practical. Optimization of signalized intersections for optimal use of the network capacity is proposed as a useful solution to resolve an important part of the problems developed at intersections. In this paper, with the aim of assessing the algorithms proposed for controlling signalized intersections and given the real potentials of common sensors present in traffic control systems, a suitable simulation medium called Signalized Intersection Fuzzy-Real Control (SIFRC) has been designed and implemented. Through the possibility made, the Abshar intersection in Isfahan city was modeled and phased through six methods: fixed time, pre-time control, segmental pre-time, fuzzy, real-time, and fuzzy-real. The results indicated better performance of the fuzzy-real method compared to the fixed time method up to 50%, and up to 10% compared to other methods. In addition, the speed of achieving the optimal response in the fuzzy-real method has been 11 times as large as that of the real-time method, while the delay time developed by the intersection in this method did not increase compared to the real-time method.