Work

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

Year: 2024

Type: article

Abstract: 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.

Source: IEEE Transactions on Intelligent Vehicles

DOI: 10.1109/tiv.2024.3504818

Authors: Edwin Solano-Araque, Guillaume Colin, Guy-Michel Cloarec, Abdel-Djalil Ourabah, Yann Chamaillard

Institutions: Renault (France), Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique, Institut National des Sciences Appliquées Centre Val de Loire, Institut National des Sciences Appliquées de Lyon, Université d'Orléans, Dassault Systèmes (France)

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W4404627664

FWCI: 0.158

Cites:

Cited by: 1

Related to: 10