Work

Energy-Efficient Cooperative Decision-Making for CAVs: A Traffic Flow Optimization Approach

Year: 2025

Type: conference-paper

Abstract: The deployment of Connected and Automated Vehicles (CAVs) has the potential to significantly improve traffic flow and decrease both congestion and fuel consumption. This study examines how speed management strategies employed by CAVs influence fuel consumption. We introduce a cooperative decision-making framework for CAVs navigating in unsignalized intersections for traffic flow optimization, utilizing the Predicted Inter-Distance Profile (PIDP). Building upon this framework, we have developed a fuel consumption model to establish a balanced optimization approach for a strategy that is both time- and energy-efficient, while guaranteeing the safety of the vehicles. The obtained results indicate that the proposed approach not only effectively reduces crossing time, but also significantly lowers fuel consumption. Through simulations of diverse random scenarios, we validate the proposed method's reliability and energy efficiency.

Source: Annual System of Systems Engineering Conference (SoSE)

DOI: 10.1109/sose66311.2025.11083785

Authors: Shan He, Lounis Adouane

Institutions: Université de Technologie de Compiègne, Centre National de la Recherche Scientifique, Heuristics and Diagnostics for Complex Systems

Language: English

Topic: Traffic control and management

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy, Sustainable cities and communities

Open Access status: green

Funder: Université de Technologie de Compiègne