At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.
Optimal Speed Control of Hybrid Electric Vehicles