Dynamic Eco-Driving for Signalized Arterial Corridors and Its Indirect Network-Wide Energy/Emissions Benefits

摘要

There are various strategies being considered to reduce fuel consumption and emissions from the transportation sector. From the transportation operations perspective, one strategy that has gained interest worldwide is eco-driving. Eco-driving typically consists of changing a person's driving behavior based on providing general advice to the driver, such as accelerating slowly, driving smoothly, and reducing high speeds. More advanced dynamic eco-driving provides real-time advice to drivers based on changing traffic and infrastructure conditions for even greater fuel and emission savings. The concept of dynamic eco-driving takes advantage of real-time traffic sensing and infrastructure information, which can then be communicated to a vehicle with a goal of reducing fuel consumption and emissions. This article considers dynamic eco-driving in an arterial corridor with traffic control signals, where signal phase and timing (SPaT) information of traffic lights is provided to the vehicle as it drives down the corridor. The vehicle can then adjust its velocity while traveling through the corridor with the goal of minimizing fuel consumption and emissions. A dynamic eco-driving velocity planning methodology has been developed and is described herein. This algorithm has then been extensively tested in simulation, showing individual vehicle fuel consumption and CO_2 reductions of around 10-15%, depending on corridor parameters including traffic volume, traffic speed, and other factors. This 10-15% improvement is realized directly by the vehicle that is equipped with this dynamic eco-driving technology and can be accomplished with very little time loss. We have also carried out an extensive analysis of the entire traffic stream under different traffic volumes and different penetration rates of the dynamic eco-driving technology. It is found that there are also significant indirect network-wide energy and emissions benefits on the overall traffic, even at low penetration rates of the technology-equipped vehicles. Based on the simulation results, the maximum fuel saving and emission reduction occur during medium traffic volumes (corresponding to traffic volume of 300 vehicles/hr/link) and with low penetration rates (5%, 10%, and 20%). Under these conditions, the total traffic energy/emissions savings typically triple what is saved from the technology-equipped vehicles alone (e.g., total 4% savings compared to 1.3% savings). This is due primarily to the eco-driving velocity planning affecting nonequipped vehicles that follow behind.