Study on Intersection Management assuming Self-Driving Cars

Abstract

The widespread adoption of self-driving cars brings new possibilities for traffic control at intersections. In this paper, we use traffic simulation (SUMO) to investigate the challenges of current traffic control methods in the context of self-driving cars and propose a new traffic control method aimed at improving traffic flow. Specifically, the method utilizes information from each vehicle attempting to enter the intersection to enhance time efficiency. By comparing the proposed method with existing traffic control methods using the simulator, we demonstrate its superior time efficiency, paving the way for more effective intersection management in an era of self-driving cars.