Towards a Real-Time Automated Eco-Driving Algorithm Based on Human Cognition With Drivability Constraints

Driving automation offers a great potential for reducing environmental impact of road transports. Automated eco-driving, i.e. adapting vehicle behaviour in order to reduce energy consumption is a way of achieving it. However, for an eco-driving algorithm to be implemented in a commercial vehicle some constraints on drivability, safety and computing power are to be addressed. In this paper, we propose an acceleration maneuver model allowing to explicitly consider drivability constraints. The model is based on many empirical studies on Physiology and Ergonomics and has been verified using real driving recordings. Then we propose an Automated Eco-driving algorithm, allowing to minimize driving energy consumption while meeting drivability and safety constraints. The algorithm is able to adapt to changes in the driving scenario and its architecture is compatible with a real-time implementation.