Compact Cooperative Adaptive Cruise Control for Energy Saving: Air Drag Modelling and Simulation

TL;DR

This paper investigates how vehicle-to-vehicle communication and robust model predictive control can enhance energy efficiency in connected automated vehicles by optimizing inter-vehicle gaps and accounting for uncertainties.

Contribution

It introduces a novel control framework that combines V2V communication with robust model predictive control for energy-efficient CACC.

Findings

V2V communication improves energy savings in CAVs.

Small inter-vehicle gaps lead to significant energy reduction.

The proposed control method effectively manages uncertainties.

Abstract

This paper studies the value of communicated motion predictions in the longitudinal control of connected automated vehicles (CAVs). We focus on a safe cooperative adaptive cruise control (CACC) design and analyze the value of vehicle-to-vehicle (V2V) communication in the presence of uncertain front vehicle acceleration. The interest in CACC is motivated by the potential improvement in energy consumption and road throughput. In order to quantify this potential, we characterize experimentally the relationship between inter-vehicular gap, vehicle speed, and (reduction of) energy consumption for a compact plug-in hybrid electric vehicle. The resulting model is leveraged to show efficacy of our control design, which pursues small inter-vehicle gaps between consecutive CAVs and, therefore, improved energy efficiency. Our proposed control design is based on a robust model predictive control framework to systematically account for the system uncertainties. We present a set of thorough simulations aimed at quantifying energy efficiency improvement when vehicle states and predictions exchanged via V2V communication are used in the control law.