Life Cycle Assessment of Connected and Automated Vehicles: Sensing and Computing Subsystem and Vehicle Level Effects

CSS Publication Number: 
CSS18-06
Abstract: 

Although recent studies of connected and automated vehicles (CAVs) have begun to explore the potential energy and greenhouse gas (GHG) emission impacts from an operational perspective, little is known about how the full life cycle of the vehicle will be impacted. We report the results of a life cycle assessment (LCA) of Level 4 CAV sensing and computing subsystems integrated into internal combustion engine vehicle (ICEV) and battery electric vehicle (BEV) platforms. The results indicate that CAV subsystems could increase vehicle primary energy use and GHG emissions by 3-20% due to increases in power consumption, weight, drag, and data transmission. However, when potential operational effects of CAVs are included (e.g., eco-driving, platooning, and intersection connectivity), the net result is up to a 9% reduction in energy and GHG emissions in the base case. Overall, this study highlights opportunities where CAVs can improve net energy and environmental performance.

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Research Areas: 
Keyword: 
connected and automated vehicle (CAV)
Publication Type: 
Journal Article
Environmental Science & Technology
Date Published: 
March 6, 2018
Persistent URL: 
http://dx.doi.org/10.1021/acs.est.7b04576
Full Citation: 
Gawron, James, Gregory Keoleian, Robert De Kleine, Timothy Wallington, and Hyung Chul Kim. (2018) “Life Cycle Assessment of Connected and Automated Vehicles: Sensing and Computing Subsystem and Vehicle Level Effects.” Environmental Science & Technology 52(5):3249–3256.
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Publication Status: 
Published