Scholarly record

OPTIMIZATION OF TRAFFIC LIGHT CONTROL USING FUZZY LOGIC

Aleksandr Shajkin, Tatyana Khlynova, О. В. Аверина, Marina Meladze, Olga Kladovshchikova

Abstract

Traffic congestion is an important problem in transport systems. The reason for traffic jams is the growing number of vehicles. It is objective and irreparable. Many roads do not have the ability to separate at different levels and have to cross. Most intersections use traffic lights to regulate traffic. Traffic light regulation is a non-stationary, non-linear problem under conditions of uncertainty. Most traffic lights nowadays use fixed time intervals. It is necessary that traffic lights monitor traffic flows at intersections and take into account changes in traffic flow over time. The use of fuzzy logic allows us to use the same rules that a person would use in a manual regulation. However, in addition to the rules (knowledge), a person has vision (input data). Unfortunately, at a particular intersection, it is not always possible to implement the data collection system that was assumed by the developer of the traffic light control algorithm. This paper proposes an adaptive traffic light control system using fuzzy logic. This system is able to take into account different types of input data, change the duration of the green light, change the sequence of its switching on for different directions, change the traffic flows, combined in one green cycle. We tested the performance of the proposed traffic light control system on a model of an intersection and it showed good results in comparison with a fixed traffic light control system.

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DOI resolver: doi.org/10.5593/sgem2021/2.1/s07.16

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