Connectivity and Automation as Enablers for Energy-Efficient Driving and Road Traffic Management

Othman, Bassel; De Nunzio, Giovanni; Sciarretta, Antonio; Di Domenico, Domenico; de Wit, Carlos Canudas · 2021 · OpenAlex-citations

DOI: 10.1007/978-1-4614-6431-0_128-1

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Summary

This paper reviews how connectivity and automation in vehicles (CAVs) can serve as enablers for energy-efficient driving and road traffic management. The research is motivated by the fact that transportation remains a major source of carbon emissions, particularly in OECD countries where it accounts for approximately 25% of total CO2 emissions. While projections suggest improved energy efficiency could lead to a net decline in energy use, the impact of CAVs on fuel consumption remains uncertain, with estimates ranging from a 90% decrease to a 200% increase compared to a 2050 baseline. The authors aim to clarify these potentials by examining control strategies that leverage Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. The study analyzes three primary control frameworks: individual vehicle optimization ("individual gain"), cooperative vehicle control ("common good"), and infrastructure control. For individual optimization, the paper details eco-routing and eco-driving strategies. Eco-routing involves selecting paths that minimize energy consumption rather than just distance or time, utilizing physical or data-driven models to predict fuel usage based on road grade, traffic, and speed limits. Eco-driving focuses on optimizing speed profiles to reduce aerodynamic drag and acceleration losses. The authors highlight that CAVs can achieve significant savings by anticipating traffic light signals (Green Light Optimal Speed Advice) and adjusting speed to maintain constant velocity, thereby avoiding stop-and-go cycles. Regarding cooperative control, the paper explores vehicle platooning and coordinated maneuvers. By communicating with neighboring vehicles, CAVs can reduce aerodynamic drag through close following distances and coordinate acceleration and braking to smooth traffic flow. This "common good" approach mitigates conflicts and improves overall network efficiency, which is difficult to achieve with human-driven vehicles due to reaction time delays and lack of precise coordination. The review also covers infrastructure control, where traffic management systems use connectivity to adjust variable speed limits and adaptive traffic light controls to optimize energy usage across urban networks. The significance of this work lies in its comprehensive synthesis of how CAV technologies can be explicitly regulated for environmental benefits. The authors conclude that while CAVs offer substantial potential for reducing energy consumption through precise control and anticipation, the net impact depends heavily on policy decisions and the specific control strategies implemented. The paper underscores the need for robust, real-time optimization algorithms and highlights that high penetration rates of CAVs are necessary to fully realize system-wide energy savings. It provides a foundational overview for future research on integrating environmental considerations into transportation regulation and control frameworks.

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Topics

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• v2x connected vehicle
• eco driving