Refined Traffic Flow Model Based on Cellular Automaton Under Cooperative Vehicle Infrastructure System

The cell size in the classical cellular automaton-based traffic flow model makes it difficult to express the position relationship of vehicles accurately. Therefore, a scheme to improve the symmetric two-lane cellular automaton (STCA) model by refining the cell size was presented. Firstly, the position, speed, acceleration, and interaction of vehicles in the urban road two-lane environment were analyzed, and the numerical model of these characteristics was built based on the cellular automaton. Especially, the road size and the cellular representation form in the model were improved to solve the problem that the existing traffic flow model based on cellular automaton does not conform to the vehicle driving phenomenon on the actual road. Secondly, according to the real vehicle infrastructure environment, road congestion, lane changing, and other behaviors in the STCA model were redefined, and the lane rules were combined with the refined lane model. A new traffic flow model, namely STCA-CH, was established. Finally, the model was compared with STCA, STCA-I, STCA-S, and STCA-M models, and the validity of the STCA-CH model was verified by analyzing the average speed, average flow, lane changing frequency, and space-time diagram under different vehicle densities. The results show that the lane changing frequency of the STCA-CH model is about 21.14% higher than that of the STCA-M model, and the maximum average flow is about 25.76%, 11.30%, and 3.75% higher than that of the STCA-I, STCA-S, and STCA-M models respectively. © 2025 Science Press. All rights reserved.