A Hybrid Autonomous Intersection Management for Minimizing Delays Using Fuzzy Logic

This research proposes a fuzzy logic model to control intersection traffic flow to reduce average delay and increase throughput. To achieve this, vehicles and the controller exchange standard Vehicle-to-Infrastructure (V2I) messages to facilitate cooperation and utilization of the intersection. The proposed approach has been validated using the F1tenth_gym_ros simulation platform and on the Eclipse Mosaic platform. The simulation results show that the proposed approach outperforms the static controllers, 25s and 30s by 35.55% and 33.15%, respectively in terms of delay minimization; and 17.44% and 17.82% in terms of throughput, respectively. The proposed approach also outperforms the state-of-the-art controller by 16.18% in terms of delay minimization and 12.16% in terms of throughput. The results of the paired sample t-test also show that the proposed controller outperforms other controllers in both delay and throughput. This shows the potential to improve intelligent transportation systems using V2X technologies and smart intersection management.