An Open Traffic Light Control Model for Reducing Vehicles\´ $\hbox {CO}_{2}$ Emissions Based on ETC Vehicles

Usually, vehicles´ stop-and-go driving will consume more fuel and emit more CO₂ than constant speed driving. To reduce vehicles´ CO₂ emissions, vehicles´ travel should be smoothed by reducing the stop-and-go times. In this paper, a three-tier structure is proposed to realize dynamic traffic light control for smoothing vehicles´ travel. In tier-1, an electronic toll collection (ETC) system is employed for collecting road traffic flow data and calculating the recommended speed. In tier-2, radio antennas are installed near the traffic lights. Road traffic flow information can be obtained by wireless communication between the antennas and ETC devices. In tier-3, a branch-and-bound-based real-time traffic light control algorithm is designed to smooth vehicles´ travels. After smoothing vehicles´ travels, more vehicles can pass intersections with less waiting time and fewer short-time stops; therefore, the vehicles´ CO₂ emissions can be reduced. Simulation results indicate that the proposed scheme performs much better than the adaptive fuzzy traffic light control method: The average waiting time, short-time stop times, and CO₂ emissions are greatly reduced, and the nonstop passing rate is greatly improved.