Intelligent control system for road intersection

An approach to the creation of intelligent object control systems using machine learning with reinforcement is illustrated using the example of an intersection control system. The simulation model of the intersection, chosen as the learning environment, is described. The results of a comparative analysis of the performance of various learning algorithms are presented. The results of applying the Monte Carlo policy gradient to train the intersection model are presented.