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:
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:
Three CAV scenarios were considered to calculate upper and lower bounds of their potential impacts on consumer costs:
- Partial: Partial automation with some connectivity
- Full-No Rideshare: Full automation with high connectivity without ridesharing
- Full-With Rideshare: Full automation with high connectivity with ridesharing.
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.
- 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.
Application Areas
Goal Areas
Keywords
None defined
Benefit ID: 2017-01176
Benefit Comments
No comments posted to date