Theses and Dissertations


Issuing Body

Mississippi State University


Ball, John E.

Committee Member

Gurbuz, Ali Cafer

Committee Member

Iqbal, Umar

Date of Degree


Document Type

Graduate Thesis - Open Access


Electrical and Computer Engineering

Degree Name

Master of Science (M.S.)


James Worth Bagley College of Engineering


Department of Electrical and Computer Engineering


Intersection Navigation plays a significant role in autonomous vehicle operation. This paper focuses on enhancing autonomous vehicle intersection navigation through advanced computer vision and Vehicle-to-Infrastructure (V2I) communication systems. The research unfolds in two phases. In the first phase, an approach utilizing YOLOv8s is proposed for precise traffic light detection and recognition, trained on the Small-Scale Traffic Light Dataset (S2TLD). The second phase establishes seamless connectivity between autonomous vehicles and traffic lights in a simulated Mississippi State University Autonomous Vehicle Simulation (MAVS) environment resembling a small city with multiple intersections. This V2I system enables the transmission of Signal Phase and Timing (SPaT) messages to vehicles, providing information on current traffic light phases and time until the next phase change which enables the vehicles to adjust their speed and behavior in real-time. The simulation demonstrates accurate traffic light detection, with vehicles receiving SPaT messages, showcasing the system’s effectiveness in a multi-intersection scenario.