Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies

Automobile manufacturers, transportation researchers, and policymakers are interested in knowing the future of connected and autonomous vehicles (CAVs). To this end, this study proposes a new simulation-based fleet evolution framework to forecast Americans’ long-term (year 2015–2045) adoption levels of CAV technologies under eight different scenarios based on 5% and 10% annual drops in technology prices; 0%, 5%, and 10% annual increments in Americans’ willingness to pay (WTP); and changes in government regulations (e.g., mandatory adoption of connectivity on new vehicles). This simulation was calibrated with data obtained from a survey of 2167 Americans, regarding their preferences for CAV technologies (e.g., WTP) and their household’s annual vehicle transaction decisions. Long-term fleet evolution suggests that the privately held light-duty-vehicle fleet will have 24.8% Level 4 AV penetration by 2045 if one assumes an annual 5% price drop and constant WTP values (from 2015 forward). This share jumps to 87.2% if one uses a 10% annual rate of decline in prices and a 10% annual rise in WTP values. Overall, simulations suggest that, without a rise in most people’s WTP, or policies that promote or require technologies, or unusually rapid reductions in technology costs, it is unlikely that the U.S. light-duty vehicle fleet’s technology mix will be anywhere near homogeneous by the year 2045.

• Record URL:
  https://doi.org/10.1016/j.tra.2016.10.013
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856415300628
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • Abstract reprinted with permission of Elsevier.
• Authors:
  • Bansal, Prateek
  • Kockelman, Kara
• Publication Date: 2017-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; Maps; References; Tables;
• Pagination: pp 49-63
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 95
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Forecasting; Intelligent vehicles; Mobile communication systems; Simulation; Stated preferences; Vehicle fleets
• Uncontrolled Terms: Adoption models; Americans; Willingness to pay
• Geographic Terms: United States
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01626079
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 15 2017 5:03PM