How do drivers use automation? Insights from a survey of partially automated vehicle owners in the United States

In this study the authors investigate how partially automated vehicles (Tesla electric vehicles with “Autopilot”) are used, including how often automation is used, on what roads, in what weather, and in what traffic conditions. The authors use a latent class model to identify heterogenous classes of autopilot users, then they use a multinomial logistic regression model to understand the relationship between each latent class and several independent variables, including socio-demographics and vehicle miles travelled (VMT). The latent class model revealed four latent classes: very frequent users, who use it most frequently; frequent users, who use automation frequently in clear weather and on freeways; semi-frequent users who use it for less than half their trips and only on freeways, in clear weather, when there is no traffic; and infrequent users, who use it the least often and only in clear weather, on freeways, when there is no traffic. The multinomial logistic regression model revealed significant differences in VMT between the clusters. Very frequent and Frequent users drive close to 15,000 miles per year, whereas Semi frequent and Infrequent users drive around 10,000 miles per year. The results suggest that consumers who purchase partially automated vehicles and use them frequently may travel more.

• Record URL:
  https://doi.org/10.1016/j.tra.2019.08.008
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856419301764
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Hardman, Scott
  • Lee, Jae Hyun
  • Tal, Gil
• Publication Date: 2019-11

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 246-256
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 129
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Automobile ownership; Automobile travel; Autonomous vehicle guidance; Autonomous vehicles; Consumer behavior; Drivers; Level 2 driving automation; Logistic regression analysis; Surveys
• Geographic Terms: United States
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01717676
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 20 2019 3:12PM