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Title: Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles

Abstract

This report details a study of the potential effects of connected and automated vehicle (CAV) technologies on vehicle miles traveled (VMT), vehicle fuel efficiency, and consumer costs. Related analyses focused on a range of light-duty CAV technologies in conventional powertrain vehicles -- from partial automation to full automation, with and without ridesharing -- compared to today's base-case scenario. Analysis results revealed widely disparate upper- and lower-bound estimates for fuel use and VMT, ranging from a tripling of fuel use to decreasing light-duty fuel use to below 40% of today's level. This wide range reflects uncertainties in the ways that CAV technologies can influence vehicle efficiency and use through changes in vehicle designs, driving habits, and travel behavior. The report further identifies the most significant potential impacting factors, the largest areas of uncertainty, and where further research is particularly needed.

Authors:
 [1];  [2];  [2];  [3];  [3];  [4]
  1. Argonne National Lab. (ANL), Argonne, IL (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  4. US Dept. of Energy, Washington, DC (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1334242
Report Number(s):
NREL/TP-5400-67216
DOE Contract Number:
AC36-08GO28308
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; connected and automated vehicle technologies; CAV; vehicle automation; partial automation; full automation; connectivity; rideshare; driver assistance; fuel use; light-duty vehicles; LDV; vehicle miles traveled; VMT; fuel efficiency; fuel consumption; energy impacts; greenhouse gas emissions; GHG; consumer costs; operating costs

Citation Formats

Stephens, T. S., Gonder, Jeff, Chen, Yuche, Lin, Z., Liu, C., and Gohlke, D. Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles. United States: N. p., 2016. Web. doi:10.2172/1334242.
Stephens, T. S., Gonder, Jeff, Chen, Yuche, Lin, Z., Liu, C., & Gohlke, D. Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles. United States. doi:10.2172/1334242.
Stephens, T. S., Gonder, Jeff, Chen, Yuche, Lin, Z., Liu, C., and Gohlke, D. Tue . "Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles". United States. doi:10.2172/1334242. https://www.osti.gov/servlets/purl/1334242.
@article{osti_1334242,
title = {Estimated Bounds and Important Factors for Fuel Use and Consumer Costs of Connected and Automated Vehicles},
author = {Stephens, T. S. and Gonder, Jeff and Chen, Yuche and Lin, Z. and Liu, C. and Gohlke, D.},
abstractNote = {This report details a study of the potential effects of connected and automated vehicle (CAV) technologies on vehicle miles traveled (VMT), vehicle fuel efficiency, and consumer costs. Related analyses focused on a range of light-duty CAV technologies in conventional powertrain vehicles -- from partial automation to full automation, with and without ridesharing -- compared to today's base-case scenario. Analysis results revealed widely disparate upper- and lower-bound estimates for fuel use and VMT, ranging from a tripling of fuel use to decreasing light-duty fuel use to below 40% of today's level. This wide range reflects uncertainties in the ways that CAV technologies can influence vehicle efficiency and use through changes in vehicle designs, driving habits, and travel behavior. The report further identifies the most significant potential impacting factors, the largest areas of uncertainty, and where further research is particularly needed.},
doi = {10.2172/1334242},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Nov 01 00:00:00 EDT 2016},
month = {Tue Nov 01 00:00:00 EDT 2016}
}

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