Variability of factors driving shared autonomous vehicle adoption: A cross-group analysis based on local ride-sharing access and historical experience

The expansion of shared autonomous vehicles (SAVs) is expected to reshape future urban mobility, yet adoption levels may differ depending on prior exposure to shared mobility services. This study investigates how local access to and experience with ride-sharing services shape the determinants of SAV adoption. Using a large stated-preference dataset, three traveler groups were identified based on their neighborhood ride-sharing conditions. To capture unobserved heterogeneity and improve explanatory power, an advanced mixed logit model with heterogeneity in both means and variances was applied. The results show that frequent public transit users and households with children exhibit a higher likelihood of adopting SAVs, whereas retired individuals, multi-vehicle households, and prospective private AV owners are less willing to adopt. Importantly, the impacts of age and vehicle size preference vary significantly across the three groups, revealing meaningful differences that would be overlooked in a pooled model. For those without local ride-sharing access or experience, older adults’ adoption tendency increases with higher income, demonstrating unique behavioral heterogeneity. By uncovering these cross-group differences, the findings highlight the need for targeted policy interventions that reflect varying user contexts. This study contributes new empirical evidence on the role of shared mobility familiarity in shaping autonomous vehicle adoption and offers actionable insights for promoting more sustainable, shared autonomous transport systems.