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

Othman, Bassel; De Nunzio, Giovanni; Lakshmanan, Vinith Kumar; Sciarretta, Antonio; Canudas-de-Wit, Carlos · 2024 · Crossref

DOI: 10.1007/978-1-4614-6431-0_128-2

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Summary

This presentation by Nicholas Chase of the U.S. Energy Information Administration (EIA) examines the potential energy implications of autonomous vehicles (AVs) within the context of the Annual Energy Outlook 2018 (AEO2018). The research is motivated by the fact that on-road vehicles accounted for 31% of delivered U.S. energy consumption in 2017, making the energy effects of AV adoption significant. The paper outlines definitions of vehicle automation, potential benefits such as improved safety and efficiency, and obstacles including consumer acceptance and cybersecurity. It highlights that AVs could either reduce energy use through eco-driving and platooning or increase it through induced travel and empty miles, with potential changes in light-duty vehicle travel demand ranging from -75% to +200%. The study utilizes three scenarios from the AEO2018 to model these impacts: a Reference case, an Autonomous Battery Electric Vehicle (BEV) case, and an Autonomous Hybrid Electric Vehicle (HEV) case. In the Reference case, AVs constitute 1% of new light-duty vehicle sales by 2050, are powered by conventional gasoline engines, and are used intensively (65,000 miles/year). The two alternative scenarios assume a more widespread adoption, with AVs comprising 31% of new sales by 2050. These scenarios also incorporate high electrification rates (96% of fleet AVs are electric/hybrid by 2050) and include automation technologies for commercial trucks enabling platooning. All scenarios assume AVs affect mass transit usage, generally increasing commuter rail use while decreasing transit bus and rail usage. The results indicate that transportation energy consumption is higher in the BEV and HEV cases compared to the Reference case due to increased vehicle miles traveled (VMT). Specifically, light-duty VMT is projected to be 14% above the Reference case in 2050 and 35% higher than 2017 levels. However, despite the increase in travel, total light-duty vehicle energy consumption in 2050 is projected to be 23% to 29% lower than 2017 levels. This reduction is driven by the shift toward more fuel-efficient electric and hybrid powertrains, which raise new vehicle compliance fuel economy. While transportation energy consumption rises relative to the Reference case, it remains below 2017 historical levels. The analysis also shows that automation assumptions significantly alter mass transit energy consumption patterns, particularly for commuter rail and transit buses. The significance of these findings lies in demonstrating that while autonomous vehicles may induce more travel, the concurrent shift toward electrification can still yield substantial net energy savings compared to current baselines. The paper underscores the uncertainty in AV impacts, noting that outcomes depend heavily on adoption rates, vehicle powertrains, and usage patterns. It provides a quantitative framework for understanding how automation and electrification interact to shape future U.S. transportation energy demand.

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