Coordinating Multiple Traffic Lights with Fog Computing and V2X Communications for Efficient Traffic Management

The global increase in the number of vehicles has exacerbated problems like traffic congestion, long travel times, harmful emissions and fossil fuel consumption. Traditional traffic control cannot deal with this increasing traffic density and its dynamic variations throughout the day. To address this challenge, we propose a Smart Traffic Light (STL) algorithm that dynamically adjusts the phases of traffic lights at intersections based on real-time traffic density. The system is based on the Fog Computing paradigm and uses Roadside Units (RSUs) to collect vehicle data and map intersections. This information is shared with a Fog Node that dynamically determines the optimal traffic light phases for the intersection within its control area. Additionally, the system enables coordination between adjacent intersections to improve traffic flow efficiency throughout its actuation area. The proposed approach was examined using the Eclipse MOSAIC framework with the SUMO mobility simulator to evaluate the impact of dynamic traffic light control and intersection coordination. Under the specific conditions and parameters tested, the results demonstrate that the STL algorithm significantly reduces average trip duration, waiting times, emissions, and fuel consumption compared to static traffic light systems. In the specific simulation setup used, enabling intersection coordination further improved efficiency — reducing trip duration by 17%, waiting times by 30%, and emissions and fuel consumption by approximately 17%. These values reflect the tested scenario and may vary with different road geometries or traffic conditions.