MODELING AND INVESTIGATION OF TRANSPORT FLOWS USING CELLULAR AUTOMATA

Abstract

The article is devoted to the possibility of controlling traffic flows by means of a controllable traffic light that directs them in the required direction based on the congestion level of main roads. Traffic lights play a key role in ensuring road safety and reducing the number of conflict situations among different road users. They help regulate traffic flows, improve traffic organization at intersections, and provide smoother and safer movement for both drivers and pedestrians. The main function of traffic lights is to coordinate the movement of vehicles and pedestrians by providing clear signals indicating when to move and when to stop. Their overarching goal remains the same – to ensure safety and orderliness on the roads. However, experimenting with a real traffic light system is considered infeasible, and the data analysis process is rather laborintensive. Modeling can be used to address this problem. The aim of this study is to develop an adaptive algorithm for controlling the operating mode of a traffic light based on a cellular automata model. To achieve this, it was necessary to investigate a traffic flow model to optimize traffic light operation as well as corresponding models that enable multi-criteria optimization. In the course of the study, a cellular automaton-based intersection model was constructed. An adaptive traffic light control algorithm was proposed and its optimal parameters were determined. The effectiveness of both the classical and adaptive traffic light control algorithms was evaluated for different numbers of vehicles. The numerical indicators used for comparison were the time required to fully clear the intersection and the vehicle idle time. The developed algorithm helps reduce the time vehicles spend at an intersection, increases the throughput capacity of the traffic light, and correspondingly decreases the impact of exhaust fumes on the environment.