CAV Optimal Scheduling Method for Unsignalized Intersections Based on Rolling Ant Colony Algorithm

With the development of intelligent networking technology and autonomous driving technology, how to efficiently and safely schedule intelligent networked autonomous vehicles at signalless intersections has become a research hotspot in traffic management. Based on this, this article first designs an objective function that considers both intersection traffic efficiency and intersection traffic safety, taking into account constraints such as safe distance, speed, acceleration, etc., and constructs a signal free intersection CAV traffic scheduling model. On this basis, a model solving algorithm based on rolling ant colony algorithm is proposed. Simulation experiments show that compared with typical signal control methods, this method can significantly improve intersection traffic efficiency and reduce the number of conflicts.