Civil Engineering Faculty Publications

Document Type

Article

Publication Date

11-2026

Abstract

As cities strive to innovate mobility while advancing sustainability, the emergence of autonomous vehicles (AVs) raises critical questions for transportation planning and policy. One question is whether they will be adopted as privately owned vehicles or shared on-demand services (robo-taxis), each with distinct implications for congestion and urban form. This study examines preferences for AV ownership versus robo-taxi use, focusing on the role of prior exposure to AV technology (AV awareness). Using datasets from Los Angeles (LA) and San Francisco (SF), we estimate a recursive bivariate ordinal probit model that jointly captures the ownership–sharing preference and AV awareness, explicitly accounting for endogeneity in awareness. To capture taste heterogeneity, we incorporate psychometric latent constructs, which are estimated via structural equation modeling, explaining pro-AV attitude and shared mobility enthusiasm. Results reveal clear geographic heterogeneity. In SF, higher AV awareness shifts preferences toward private ownership rather than SAV, indicating that awareness-building can unintentionally reinforce ownership pathways. In LA, awareness is not a significant predictor of the ownership–sharing preference. Across both cities, stronger pro-AV attitudes consistently favor ownership. Shared mobility enthusiasm increases robo-taxi preference in LA but not in SF, suggesting that shared-mobility habits translate into SAV openness more strongly in LA. Overall, the findings emphasize that AV policy should treat awareness as a behavioral mechanism, not merely a covariate, and pair awareness initiatives with explicit shared-use framing and locally tailored strategies to support sustainable and equitable autonomous mobility transitions in future cities.

Comments

Original published version available at https://doi.org/10.1016/j.cities.2026.107354

Publication Title

Cities

DOI

10.1016/j.cities.2026.107354

Available for download on Saturday, July 01, 2028

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