Life Cycle Assessment of Connected and Automated Vehicles: Sensing and Computing Subsystem and Vehicle Level Effects
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.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The production and operation of ICT systems may substantially offset the benefits from automated driving, platooning and other energy-saving operations enabled by ICT systems.
“Similarly, the production and operation of information and communication technology (ICT) systems may substantially offset the benefits from automated driving, platooning and other energy-saving operations that are enabled by these ICT systems [121, 122].”
From Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics—a review (2019) · cites this paper as [121]
Through trip-chaining, autonomous taxis could radically reduce the number of vehicles required, potentially at the cost of increased vehicle turn-over and longer distances.
“Through trip-chaining, autonomous taxis (ATs) could radically reduce the number of vehicles required, potentially at the cost of increased vehicle turn-over and longer distances.”
From Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics—a review (2019) · cites this paper as [121]
Only a fraction of the increasing amount of electronics is recycled as electronic parts are distributed throughout the car and are not easily collected.
“Only a fraction of the increasing amount of electronics is recycled as electronic parts are distributed throughout the car, as these parts are not easily collected [121,174].”
From Material efficiency strategies to reducing greenhouse gas emissions associated with buildings, vehicles, and electronics—a review (2019) · cites this paper as [121]
Cites
Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations
Fagnant, D. J., & Kockelman, K. (2015) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.04.003 · Cited by 3,214 · see citing works
Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles
Wadud, Z., MacKenzie, D., & Leiby, P. (2016) · Transportation Research Part A: Policy and Practice · doi:10.1016/j.tra.2015.12.001 · Cited by 859 · see citing works
Cradle-to-Gate Emissions from a Commercial Electric Vehicle Li-Ion Battery: A Comparative Analysis
Kim, H. C., Wallington, T. J., Arsenault, R., Bae, C., Ahn, S., & Lee, J. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b00830 · Cited by 312 · see citing works
Self-citationAutonomous Driving in the iCity—HD Maps as a Key Challenge of the Automotive Industry
Seif, H., & Hu, X. (2016) · Engineering · doi:10.1016/j.eng.2016.02.010 · Cited by 277 · see citing works
An Analysis of Possible Energy Impacts of Automated Vehicles
Brown, A., Gonder, J., & Repac, B. (2014) · Lecture Notes in Mobility · doi:10.1007/978-3-319-05990-7_13 · Cited by 217 · see citing works
Life Cycle Assessment of Diesel and Electric Public Transportation Buses
Cooney, G., Hawkins, T. R., & Marriott, J. (2013) · Journal of Industrial Ecology · doi:10.1111/jiec.12024 · Cited by 161 · see citing works
Kim, H. C., & Wallington, T. J. (2016) · Environmental Science & Technology · doi:10.1021/acs.est.6b02059 · Cited by 125 · see citing works
Self-citationComparing Embodied Greenhouse Gas Emissions of Modern Computing and Electronics Products
Teehan, P., & Kandlikar, M. (2013) · Environmental Science & Technology · doi:10.1021/es303012r · Cited by 96 · see citing works
Framework for Analyzing Transformative Technologies in Life Cycle Assessment
Miller, S. A., & Keoleian, G. A. (2015) · Environmental Science & Technology · doi:10.1021/es505217a · Cited by 87 · see citing works
Self-citationA comprehensive framework for automotive sustainability assessment
Jasiński, D., Meredith, J. O., & Kirwan, K. (2016) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2016.07.027 · Cited by 85 · see citing works
Impact of Connectivity and Automation on Vehicle Energy Use
Michel, P., Karbowski, D., & Rousseau, A. P. (2016) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2016-01-0152 · Cited by 39 · see citing works
CAAD: Computer Architecture for Autonomous DrivingPreprint
Liu, S., Tang, J., Zhang, Z., & Gaudiot, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1702.01894 · Cited by 24 · see citing works
Fuel consumption impacts of auto roof racks
Chen, Y., & Meier, A. (2016) · Energy Policy · doi:10.1016/j.enpol.2016.02.031 · Cited by 22 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Hertwich, E. G., Ali, S., Ciacci, L., Fishman, T., Heeren, N., Masanet, E., Asghari, F. N., Olivetti, E., Pauliuk, S., Tu, Q., et al. (2019) · Environmental Research Letters · doi:10.1088/1748-9326/ab0fe3 · Cited by 477 · see citing works
Review and Meta-Analysis of EVs: Embodied Emissions and Environmental Breakeven
Dillman, K. J., Árnadóttir, Á., Heinonen, J., Czepkiewicz, M., & Davíðsdóttir, B. (2020) · Sustainability · doi:10.3390/su12229390 · Cited by 77 · see citing works
da Costa, V. B. F., Bitencourt, L., Dias, B. H., Soares, T., de Andrade, J. V. B., & Bonatto, B. D. (2025) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2024.114988 · Cited by 43 · see citing works
2022 roadmap on neuromorphic computing and engineering
Christensen, D. V., Dittmann, R., Linares-Barranco, B., Sebastian, A., Le Gallo, M., Redaelli, A., Slesazeck, S., Mikolajick, T., Spiga, S., Menzel, S., et al. (2022) · Neuromorphic Computing and Engineering · doi:10.1088/2634-4386/ac4a83
- Authors
- Gawron, J. H., Keoleian, G. A., De Kleine, R. D., Wallington, T. J., & Kim, H. C.
- Affiliations
- University of Michigan (US)
- Research and Innovation Center, Ford Motor Company, Dearborn, Michigan 48121, United States
- Ford Motor Company (United States) (US)
- Corresponding author
- Keoleian, Gregory A.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-02-15
- Volume
- 52
- Issue
- 5
- Pages
- 3249-3256
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W2787340708
- Cited by
- 217
- References
- 13
- Citations by year
- 2026: 17 · 2025: 12 · 2024: 24 · 2023: 32 · 2022: 31 · 2021: 23 · 2020: 40 · 2019: 31 · 2018: 7
- FWCI
- 9.64
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Environmental Science & Technology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Michigan (N022546-00)
- Ford Motor Company (N022546-00)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
- Physical Sciences › Environmental Science › Environmental Engineering › Environmental Impact and Sustainability
- Keywords
- connected and automated vehicles, Level 4 automation, battery electric vehicles, internal combustion engine vehicles, greenhouse gas emissions, primary energy consumption, eco-driving, vehicle platooning
- MeSH terms
- Automobile Driving, Vehicle Emissions, Electricity, Electric Power Supplies, Greenhouse Effect
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
