Ant Colony Algorithm in Traffic Flow Control

Abstract

The relevance of the research is determined by the need to optimize traffic light control at intersections to reduce congestion and delays and increase the capacity of intersections. A practical solution to this problem is using intelligent transport systems and specific decision-making subsystems. However, automating such tasks requires scientific research to develop effective algorithms suitable for practical use. This work proposes an approach to optimizing traffic light control at intersections that considers the traffic flow parameters at a specific intersection and those at adjacent intersections, utilizing an ant colony optimization algorithm to optimize traffic light control at neighboring intersections. The results obtained show that this approach is more effective compared to existing methods and has the potential to reduce delays by 10% and increase intersection capacity by 15% and more.