Heterogeneous Preferences for Activities While Traveling in Autonomous Vehicles: Relationships With Travel Contexts and Attitudes

Although the literature on autonomous vehicles (AVs) has been growing with a focus on adoption, expected changes in travel behavior, and travel demand and land use in the future, few studies have analyzed envisioned activities in AVs, which will affect all those outcomes at the micro level. To address this gap, this study examines preferred activities in autonomous vehicles (AVs), and especially their heterogeneity. In doing so, it uses a rich survey dataset (N=3,376), collected in four regions of the southern United States from June 2019 to March 2020 and weighted to be representative of the study population on key sociodemographic features. A latent-class cluster analysis (LCCA) enables us to identify a few distinctive combinations of preferred in-vehicle activities, separately for one group of respondents with respect to hypothetical alone trips (N=1,995) and for another group with respect to family trips (N=1,381). The alone-trip model uncovers Active use of time (37.6%), Passive use of time (19.9%), Alert (23.8%), and No-ride (18.7%) classes. Similarly, the family-trip model reveals Active use of time (35.3%), Relax and interact (18.8%), Alert and interact (32.1%), and No-ride (13.9%) classes. As for underlying factors affecting individuals' class membership, travel contexts, attitudes (e.g., tech-savviness, trust in AV technology, appreciation of varied benefits of AVs), and employment status (for alone-trip model only) account for the heterogeneity in preferences for in-vehicle activities and willingness to ride in AVs. With respect to the latter, we further examine their links to expected changes in travel behavior when AVs become available. In sum, this study investigates a wide range of in-vehicle activities (including the option of not to ride in an AV), identifies groups of activities preferred together, and explains respondents’ choices with respect to various attitudes and travel contexts.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    Department of Transportation

    1200 New Jersey Avenue, SE
    Washington, DC  United States  20590

    Office of the Assistant Secretary for Research and Technology

    University Transportation Centers Program
    Department of Transportation
    Washington, DC  United States  20590
  • Managing Organizations:

    Center for Teaching Old Models New Tricks (TOMNET)

    Arizona State University
    Tempe, AZ  United States  85287
  • Performing Organizations:

    Georgia Institute of Technology, Atlanta

    790 Atlantic Drive
    Atlanta, GA  United States  30332-0355
  • Principal Investigators:

    Circella, Giovanni

  • Start Date: 20191001
  • Expected Completion Date: 20240701
  • Actual Completion Date: 0
  • USDOT Program: University Transportation Centers Program

Subject/Index Terms

Filing Info

  • Accession Number: 01755000
  • Record Type: Research project
  • Source Agency: Center for Teaching Old Models New Tricks (TOMNET)
  • Contract Numbers: 69A3551747116
  • Files: UTC, RIP
  • Created Date: Oct 20 2020 8:51PM