Gauging Public Attitudes and Preferences Toward a Hypothetical Future Public Shared Automated Vehicle System: Examining the Roles of Gender, Race, Income, and Health

Noah Wexler, Yingling Fan

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

We use data from an originally designed survey instrument administered in the Minneapolis–St. Paul metropolitan area to gauge general attitudes and design preferences for a hypothetical shared automated vehicle (SAV) system. Design considerations include seating, payment and booking logistics, security, and extra space and amenities. We pay particular attention to the role of gender, race, health, and income in shaping these attitudes and preferences. Specifically, we use multiple regression models to uncover general willingness-to-use SAV technology, finding that women are overall less comfortable with the technology, Black and Hispanic participants are more willing to pay for SAV technology and generally display lower magnitude preferences for design considerations. Although results are mixed in both sets of analysis for health status, higher income individuals display higher willingness to pay and higher magnitude preferences for design considerations.

Original languageEnglish (US)
Title of host publicationTransportation Research Record
PublisherSage Publications Ltd
Pages588-600
Number of pages13
Volume2676
Edition10
DOIs
StatePublished - Oct 2022

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research in this paper is funded by the National Science Foundation’s Smart and Connected Communities (NSF S&CC) program. The NSF S&CC award (#1831140) is entitled Leveraging Autonomous Shared Vehicles for Greater Community Health, Equity, Livability, and Prosperity (HELP). In addition, the Center for Transportation Studies at the University of Minnesota provided in-kind support for the research in the paper.

Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2022.

Keywords

  • automated vehicles
  • operations
  • planning and analysis
  • planning for connected and automated vehicles
  • preference survey data analysis

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