A Real-time Eco-Driving Strategy for Automated Electric Vehicles

Over the past years, connected and automated vehicles (CAV) have become highly important in the transportation research field. Several prototypes are already introduced by established companies in cooperation with research centers. However, the crucial part of reducing their energy consumption by driving in an optimal way and facing external disturbances is sometimes overlooked. In this paper, we propose a safe-and eco-driving control system that enables the CAV to accelerate or to decelerate optimally while preventing both collision with preceding vehicle (i.e. disturbance) and violation of speed limitations. Optimal control problem (OCP) minimizing energy consumption for an electric vehicle while enforcing state constraints is formulated. Numerically, the problem is solved using a Model Predictive Control-like approach. The real-time implementation is possible thanks to the analytical solution of the state-constrained OCP. The proposed system is evaluated through a simulation for various driving scenarios, and it is shown that it can significantly reduce energy consumption compared to conventional driving while also avoiding the collision, without increasing arrival time.