Consumer preferences of electric and automated vehicles

In an effort to understand public acceptance and adoption behavior of smart vehicles technologies, this paper presents a detailed analysis of consumer preference for electric and autonomous vehicles. The analysis is based on the results of a recent survey conducted in the Chicago Metropolitan area. Multiple stated choice experiments are designed and the respondents are asked to choose the most preferable vehicle option to purchase among the four described alternatives: non-automated gasoline vehicle, non-automated electric vehicle, automated gasoline vehicle, and automated electric vehicle. This study adopts the random parameter logit model to estimate respondents' vehicle choice behavior while accounting for preference heterogeneity across respondents. The authors found that demographics, driving patterns, experience with technology and expectations for benefits/concerns affect participants' adoption behavior. It is also found that the possibility of imperfect performance in response to unexpected traffic situations is the most critical concern of respondents, while increased safety is the most significant expected benefit of automated vehicles. Young adults, well-educated and tech-savvy respondents, those with high annual vehicle miles of travel (VMT) and those who have long-distance work trips are found to be more willing to choose automated and electric automated options.

• Record URL:
  http://dx.doi.org/10.1109/MTITS.2017.8005606
• Supplemental Notes:
  • Copyright © 2017, IEEE.
• Corporate Authors:

  Institute of Electrical and Electronics Engineers (IEEE)

  3 Park Avenue, 17th Floor
  New York, NY  United States  10016-5997
• Authors:
  • Shabanpour, Ramin
  • Mousavi, Seyedeh Niloufar Dousti
  • Golshani, Nima
  • Auld, Joshua
  • Mohammadian, Abolfazl
• Conference:
  • 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS 2017)
  • Location: Naples , Italy
  • Date: 2017-6-26 to 2017-6-28
• Publication Date: 2017

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 716-720
• Monograph Title: 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS 2017)

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Consumer preferences; Demographics; Electric vehicles; Logits; Surveys
• Geographic Terms: Chicago Metropolitan Area
• Subject Areas: Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01747837
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 17 2020 9:32AM