Social Acceptance of Self-Driving Vehicles Across Generations and Genders: An Empirical Analysis

The rapid development of autonomous vehicle technologies represents a major transformation in contemporary transportation systems; however, their successful integration depends not only on technological maturity but also on societal acceptance. This study investigates public attitudes toward autonomous vehicles, with particular emphasis on generational and gender-based differences, aiming to identify key factors influencing acceptance, usage intention, and purchase-related decision-making. A quantitative, cross-sectional research design was applied using an online questionnaire survey conducted between January and September 2025. The final sample consisted of 655 respondents, with a balanced gender distribution and representation across multiple generational cohorts. Statistical analyses included one-way and two-way analysis of variance (ANOVA), complemented by non-parametric tests when distributional assumptions were not fully met. The results indicate significant generational differences across all examined dimensions. Younger generations, particularly Generations Y and Z, exhibit significantly higher willingness to try autonomous vehicles, greater openness to new technologies, and stronger consideration of autonomous functions in vehicle purchasing decisions. Gender-based differences were also identified, with men generally demonstrating higher technological openness than women. Moreover, a significant interaction effect between generation and gender was found, suggesting that gender differences vary across generational groups and are less pronounced among younger cohorts. Despite these contributions, the study has several limitations. Its cross-sectional design captures attitudes at a single point in time and does not allow causal inference or longitudinal analysis of attitude change. The use of self-reported, hypothetical measures may not fully reflect actual behaviour in real-world adoption scenarios. Additionally, online data collection may introduce self-selection bias, favouring respondents with higher digital literacy and technological interest. Overall, the findings highlight the importance of considering demographic heterogeneity when developing, communicating, and regulating autonomous vehicle technologies, while also underscoring the need for longitudinal and behaviour-based research in future studies.