Benefit

A USDOE study assessed the potential impacts of a nationwide deployment of connected and automated vehicles (CAV) and reported mixed results with respect to travel cost impacts; ranging from a 60 percent decrease in cost per passenger mile in scenarios with full automation and full ridesharing, to a 3-4 percent increase in cost for scenarios with partial automation.

U.S. Department of Energy (USDOE) modeling of connected and automated vehicle (CAV) impacts using multiple deployment configuration scenarios.


November 2016


Summary Information

This study conducted by the National Renewal Energy Laboratory estimated ranges of potential effects of connected and automated vehicle (CAV) technologies on vehicle miles traveled (VMT), vehicle fuel efficiency and cost to consumers.

Three CAV scenarios were considered to calculate upper and lower bounds of their potential impacts on consumer costs:
  1. Partial: Partial automation with some connectivity
  2. Full-No Rideshare: Full automation with high connectivity without ridesharing
  3. Full-With Rideshare: Full automation with high connectivity with ridesharing.
The scenario with partial automation was assumed to include technologies such as driver assistance that required an attentive driver to control the vehicle, with limited connectivity. Scenarios with full automation were assumed to allow vehicle operation without an attentive driver, with connectivity that permitted communication between travelers, vehicles, traffic control devices, and traffic control centers. Ridesharing referred to a net increase in vehicle occupancy resulting from two or more people riding together in a vehicle during some or all of their travel.

Data input into the model to evaluate potential CAV technology impacts on costs to consumers was derived from relevant information extracted from literature for separate cost categories. Costs in the following categories, spanning vehicle purchase and operation, were considered:
  • CAV technology cost increment to vehicle purchase price
  • Maintenance and repair costs
  • Connectivity service fee
  • Insurance premiums
  • Costs of crashes not covered by insurance
  • Fuel cost
  • Cost of travel time.
Findings
  • Compared to the conventional baseline, most CAV scenarios showed substantial decreases in costs to consumers.
  • The lower end assumptions in the "Full-With Rideshare" scenario generated the largest estimated cost reduction (roughly 60 percent relative to the base scenario on a cost per passenger mile basis, when accounting for the cost of travel time).
  • The upper-end assumptions for the Partial automation scenario produced the only cost increasing case relative to the baseline. For this case, assumptions of higher vehicle purchase price and repair costs together with little or no benefits with respect to insurance and travel time costs resulted in a net 3 to 4 percent cost increase relative to the baseline.

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Source

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

Author: T.S. Stephens (Argonne National Laboratory); J. Gonder and Y. Chen (National Renewable Energy Laboratory); Z. Lin and C. Liu (Oak Ridge National Laboratory); D. Gohlke (U.S. Department of Energy)

Published By: National Renewable Energy Laboratory

Source Date: November 2016

Other Reference Number: NREL/TP-5400-67216

URL: https://www.nrel.gov/docs/fy17osti/67216.pdf

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Goal Areas

Productivity

Keywords

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Benefit ID: 2017-01176