An Eco-Driving Strategy for Partially Connected Automated Vehicles at a Signalized Intersection

We consider a signalized intersection under a partially connected automated vehicle (CAV) environment. There is a control center for the control zone that needs to predict the trajectories of human driving vehicles (HDVs) and control the trajectories of CAVs. By adopting model predictive control, we propose a real-time eco-driving strategy for the control center. In the proposed strategy, the Gipps' car-following model is selected to update the acceleration of HDV and an optimal control problem (OCP) is proposed to optimize the trajectory of each CAV based on real-time travel information. The control objective is to minimize the total fuel consumption of each CAV during the current control period. Pontryagin's minimum principle is employed to derive necessary optimality conditions under different scenarios. With the necessary optimality conditions, a numerical method is developed to solve the proposed OCP. Finally, numerical examples are provided to illustrate the performance of the proposed eco-driving strategy.