  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.
