V2I communication of autonomous vehicles with traffic light infrastructures of multiple intersections to optimize vehicle speed

Vehicle-to-infrastructure (V2I) communication between autonomous vehicles and traffic light systems offers a promising approach to optimizing speed for enhanced energy efficiency, particularly when navigating through multiple intersections. This paper presents a framework where autonomous vehicles communicate with traffic light infrastructures at consecutive multiple intersections to receive SPaT messages containing real-time signal timing and phase data. SPaT refers to real-time data that describe the current state, timing, and phase information of traffic signals at intersections, including the current color (red, yellow, or green) and the remaining time before the signal changes. Using this information, the system dynamically adjusts vehicle speed to minimize unnecessary stops, idling, and acceleration, thus reducing energy consumption. The system aims to synchronize the vehicle’s speed with traffic light phases, allowing smoother movement through consecutive intersections. The proposed approach integrates advanced control algorithms and predictive modeling to adjust vehicle movements with traffic light phases to pass through all intersections smoothly. In this paper, a low-fidelity simulation has been developed in MATLAB RoadRunner to establish a V2I communication with multiple consecutive traffic lights. A small city with multiple intersections has been designed where traffic lights are controlled. Then, V2I Communication has been established between the autonomous vehicle and three consecutive intersection traffic lights to control the vehicle’s speed. During the simulation, the autonomous vehicle successfully received SPAT messages and adjusted its speed in response, navigating through three intersections without compromising traffic flow or safety. This work highlights the potential of V2I communication to optimize speed while autonomous vehicles navigate through an intersection, especially in scenarios involving multiple consecutive intersections.