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

Kim, Ilsu; Lee, Yongsung; Mokhtarian, Patricia L.; Circella, Giovanni · 2024 · ROSA P / Center for Teaching Old Models New Tricks (TOMNET)

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Summary

This study addresses a critical gap in autonomous vehicle (AV) research by examining heterogeneous preferences for in-vehicle activities, which are often overlooked in analyses of AV adoption and travel behavior. While existing literature focuses on macro-level outcomes like travel demand and land use, this research investigates the micro-level mechanisms—specifically, how individuals envision using travel time when released from manual driving. The authors posit that the nature of in-vehicle activities influences the utility derived from AV trips, which in turn affects adoption rates and reshapes activity-travel patterns. To analyze these preferences, the researchers utilized a comprehensive survey dataset of 3,376 respondents collected between June 2019 and March 2020 across four southern U.S. metropolitan areas (Atlanta, Phoenix, Austin, and Tampa). The data were weighted to represent the adult population of these regions. Respondents were presented with hypothetical AV travel contexts, including solo trips (to work, stores, or long-distance) and family trips (to parks or long-distance), and asked to select up to three preferred in-vehicle activities from a list of eleven options, plus an option to refuse riding in an AV. The study employed Latent-Class Cluster Analysis (LCCA) to identify distinct groups of individuals with similar activity preferences. This method included a measurement model to uncover latent classes based on activity selection and a membership model to determine how travel contexts, attitudes (e.g., tech-savviness, trust), and sociodemographic factors influenced class membership. The results identified four distinct latent classes for both solo and family trips. For solo trips, the classes were "Active use of time" (37.6%), "Passive use of time" (19.9%), "Alert" (23.8%), and "No-ride" (18.7%). For family trips, the classes were "Active use of time" (35.3%), "Relax and interact" (18.8%), "Alert and interact" (32.1%), and "No-ride" (13.9%). The analysis revealed that travel contexts, attitudes toward AV technology, and employment status significantly account for heterogeneity in these preferences. Specifically, factors such as trust in AVs and appreciation of their benefits were linked to willingness to ride and the choice of specific activity bundles. The study further connected these preferences to expected changes in travel behavior, suggesting that how individuals utilize in-vehicle time will influence broader shifts in travel demand. The significance of this work lies in its detailed characterization of in-vehicle time use, moving beyond simple adoption metrics to understand the behavioral drivers of AV utility. By identifying specific groups of travelers and their preferred activity bundles, the study provides actionable insights for policymakers and planners. It highlights that AV impacts on travel demand and land use are mediated by individual attitudes and travel contexts, emphasizing the need for nuanced policy responses that account for heterogeneous user preferences rather than treating AV adoption as a uniform phenomenon.

Key finding

Latent-class cluster analysis identified distinct groups of AV passengers based on preferred in-vehicle activities, with class membership significantly predicted by travel contexts, attitudes toward AV technology, and employment status.

Methodology

survey

Sample size: 3376

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• acceptance adoption
• passenger motion sickness comfort

Information type

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• Empirical Findings: observational prevalence, self report data