Enhancing Traffic Flow and Safety in Mixed Vehicle Fleets: Mitigating the Influence of Non-Cooperative Vehicles on Autonomous Intersection Management Systems

With the rapid advancement of autonomous vehicle technology, integrating mixed autonomous and non-autonomous vehicles that are not cooperative in vehicular network has become a significant challenge. This paper presents an innovative Autonomous Intersection Management (AIM) system designed to optimize traffic flow and enhance intersection safety in such mixed traffic scenarios. By utilizing vehicle-to-infrastructure (V2I) communication and advanced intersection control algorithms, the AIM system showcases the potential of next-generation vehicular network technologies in revolutionizing intersection management. To evaluate the performance of the AIM system and the impact of non-cooperative vehicles, extensive simulations were conducted using realistic traffic scenarios and a mixed traffic model. The results demonstrate that the proposed system effectively enhances intersection throughput, and ensures safe and efficient operations, particularly in situations involving a high proportion of autonomous vehicles. Additionally, the system’s robustness is demonstrated by evaluating its performance under various traffic flow rates and considering imperfect wireless communication conditions.