A V2X-Based Distributed Virtual Traffic Light Scheduling Algorithm

Urban traffic congestion not only increases fuel consumption and pollution but also causes inconvenience to residents. Although traditional physical traffic light systems provide a certain solution, their reliance on complex road infrastructure results in high maintenance and installation costs. In contrast, virtual traffic light systems, as a self-organizing traffic control system, do not rely on road infrastructure. A V2X-based distributed virtual traffic light scheduling algorithm has been designed and implemented, aiming to optimize vehicle traffic efficiency and reduce CO2 emissions. The research adopts hierarchical and clustering methods, combined with a priority scheduling strategy and Look-Ahead decision tree algorithm, to improve the overall efficiency of traffic flow. Simulation results show that this method performs excellently under different traffic densities. Under balanced traffic conditions, the scheduling algorithm increases the number of vehicles passing per minute by approximately 7.31% compared to the uncontrolled system and by approximately 8.28% compared to the traditional traffic light system; it also reduces the stop-start ratio per vehicle by approximately 9.90% and 20.50%, respectively. Under unbalanced traffic conditions, the number of vehicles passing increases by approximately 9.44% and 2.91%, and the stop-start ratio decreases by approximately 7.68% and 15.10%. By reducing the stop-start ratio per vehicle, fuel consumption can be effectively lowered, thereby reducing CO2 emissions.