Simulation Research on Automatic Control System of Urban Light Rail Traffic Signal Based on Ant Colony Algorithm

In the development of urban light rail transit, the signal system of urban light rail transit plays an extremely important role and is the key part of the development of urban light rail transit. However, the huge rail transit system has high complexity, multiple variability, even the accurate mathematical model is still difficult to build, and the limitations of the scheme are difficult to match the variability of the traffic system, so the control effect is not optimistic. In this paper, the simulation research of automatic control system of urban light rail traffic signal based on ACA (Ant colony algorithm) is proposed, and the traffic signal optimization model based on ACA is established. On the basis of the basic ACA, the global update rules are improved, and the local update rules are added. The purpose of global update is to make the search process more instructive. The simulation results show that the convergence speed of the improved ACA algorithm adopted in this paper is obviously better. When the number of iterations of the algorithm is 8, the delay has converged to 97. The feasibility of improve ACA algorithm and model is proved.