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Cited by 859Vehicle emissions and performanceEnergy, Environment, and Transportation PoliciesTransportation and Mobility Innovations

The DOI matches its Crossref record; 51 of the 52 references it cites were found in a registry or an index.

Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles

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Wadud, Zia, MacKenzie, Don, Leiby, Paul·2016·Transportation Research Part A: Policy and Practice
DOI 10.1016/j.tra.2015.12.001
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Abstract

Experts predict that new automobiles will be capable of driving themselves under limited conditions within 5–10 years, and under most conditions within 10–20 years. Automation may affect road vehicle energy consumption and greenhouse gas (GHG) emissions in a host of ways, positive and negative, by causing changes in travel demand, vehicle design, vehicle operating profiles, and choices of fuels. In this paper, we identify specific mechanisms through which automation may affect travel and energy demand and resulting GHG emissions and bring them together using a coherent energy decomposition framework. We review the literature for estimates of the energy impacts of each mechanism and, where the literature is lacking, develop our own estimates using engineering and economic analysis. We consider how widely applicable each mechanism is, and quantify the potential impact of each mechanism on a common basis: the percentage change it is expected to cause in total GHG emissions from light-duty or heavy-duty vehicles in the U.S. Our primary focus is travel related energy consumption and emissions, since potential lifecycle impacts are generally smaller in magnitude. We explore the net effects of automation on emissions through several illustrative scenarios, finding that automation might plausibly reduce road transport GHG emissions and energy use by nearly half – or nearly double them – depending on which effects come to dominate. We also find that many potential energy-reduction benefits may be realized through partial automation, while the major energy/emission downside risks appear more likely at full automation. We close by presenting some implications for policymakers and identifying priority areas for further research.

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Research works printed but not linked: 7

  1. AAA, 2012. Your Driving Costs, 2012 edition, Heathrow, FL.
  2. Cambridge Systematics, 2009. Assessment of Fuel Economy Technologies for Medium and Heavy Duty Vehicles: Commissioned Paper on Indirect Costs and Alternative Approaches, Draft final paper, Cambridge Systematics Inc. (revised 21.09.09).
  3. Gladwell, M., 2004. Big and Bad: How the SUV ran over Automotive Safety. The New Yorker, Jan 12, pp. 28–33.
  4. IEEE, 2012. News release on Intelligent Transportation System. Available: <http://www.ieee.org/about/news/2012/5september_2_2012.html> (accessed Jan 2014).
  5. Tsugawa, S., 2013. Energy and Environmental Implications of Automated Truck Platooning within Energy ITS Project. TRB Road Vehicle Automation Workshop, Stanford, CA (16.07.13).
  6. Underwood, S., 2014. Automated Vehicles Forecast: Vehicle Symposium Opinion Survey. Automated Vehicles Symposium 2014, Burlingame, CA (15.07.14).
  7. White, 2010, Why 70 miles per hour is the new 55, The Wall Street J.

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Metadata

Authors
Wadud, Z., MacKenzie, D., & Leiby, P.
Affiliations
  • University of Leeds (GB)
  • University of Washington (US)
  • Oak Ridge National Laboratory (US)
Corresponding author
Wadud, Zia
ORCID
Venue
Transportation Research Part A: Policy and Practice
Publisher
Elsevier BV
Published
2016-04
Volume
86
Pages
1-18
ISSN
0965-8564 (ISSN-L)
DOI
10.1016/j.tra.2015.12.001
OpenAlex
W2259684855
Cited by
859
References
52
Citations by year
2026: 34 · 2025: 60 · 2024: 83 · 2023: 81 · 2022: 132 · 2021: 118 · 2020: 133 · 2019: 103 · 2018: 76 · 2017: 29 · 2016: 10
FWCI
63.33
Type
journal article
Language
en
Open access
Licence
Locations
  • Transportation Research Part A Policy and Practice (publishedVersion, cc-by-nc-nd)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • U.S. Department of Transportation
  • Imperial College London
  • Federal Highway Administration
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
  • Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Environment, and Transportation Policies
  • Social Sciences › Transportation › Transportation and Mobility Innovations
Keywords
highly automated vehicles, autonomous vehicles, travel demand, vehicle energy consumption, greenhouse gas emissions, energy decomposition analysis, partial automation, full automation, vehicle design, fuel selection, heavy vehicles, light-duty vehicles, road transport emissions, energy policy

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