An Algorithmic Approach to 4-way Autonomous Intersection Management

The objective of this research is to present an approach focused on optimizing intersection management, a subset of end-to-end autonomous driving. The proposed method relies on vehicle-to-vehicle (V2V) communication and an intersection signal amplifier to enhance intersection handling. This approach prioritizes improving intersection management by using V2V communication in place of conventional traffic signal intersections and also increases intersection safety while streamlining resource allocation and time efficiency. Evaluations are conducted using the microscopic traffic simulator SUMO (Simulation of Urban MObility), and the results indicate a noticeable reduction in congestion. The intended goal here is to reduce the average time taken for travel and provide travel convenience by aiming for constant speed. Therefore provides an efficient algorithm for implementing and testing autonomous intersection management strategies with autonomous driving systems, contributing to developing more efficient and safer autonomous transportation solutions.