Exploring ranked preferences for different autonomous vehicle transport options using a hybrid rank-ordered logit model

Public acceptance of autonomous vehicles (AVs) varies by vehicle type and user demographics, underscoring the need for appropriate policies and infrastructure to ensure AVs contribute effectively to sustainable transportation. Most existing research examining the factors associated with public acceptance of AVs focuses on one type such as privately owned AVs or shared AVs, overlooking preferences across ownership, public transit, and shared mobility. This study employs Multiple Indicators Multiple Causes and Hybrid Rank-Ordered Logit models to investigate the effects of latent variables on preferences toward multiple AV-based travel modes in Taiwan. Results show that preferences are shaped more strongly by sociodemographic characteristics, generational cohort, and information exposure than by income alone. Generational differences are particularly pronounced. Gender differences further underscore the importance of deploying AV strategies in a differentiated manner. Education level and employment status provide additional insights relevant to equity. Existing travel behavior plays a more nuanced role. One of the most policy-relevant contributions of this study concerns the role of information environments. The intensity of media consumption matters as much as the medium itself. Implications for the sustainable development of on-demand and automated mobility services include: AV deployment strategies should be differentiated by population segment and service type, rather than assuming homogeneous acceptance of automation; policies should explicitly address concerns related to social comfort, trust, and perceived safety in a targeted way; equity considerations call for balancing private AV ownership models with shared and publicly oriented services to avoid reinforcing social selectivity in access to automated mobility.