## 6 Conclusions  
This study examined the impact of varying levels of anthropomorphism in voice agents on the UX of young adults in autonomous vehicles. First, we categorized the voice agents into three types: Agent A (machine voice without a humanized speech strategy), Agent B (human voice without a humanized speech strategy), and Agent C (human voice with a humanized speech strategy). Our findings revealed an increase in perceived anthropomorphism from Agent A to Agent C, confirming that human-like elements significantly enhance users' perception of anthropomorphism. Second, it was observed that there were no significant differences in trust and perceived safety across the agents, indicating that these constructs are influenced by factors beyond anthropomorphism. Additionally, while Agent A had a higher intention to use compared to Agent B, and Agent C had a higher intention to use than Agent B, there was no significant difference between Agents A and C. This suggests that while humanized speech and a human voice have a positive impact on intention to use, the mechanical voice of Agent A remains appealing due to its perceived efficiency and reliability. Third, the divergence between intimacy and intention to use highlights the complexity of the UX dimensions, suggesting that a balanced approach is needed when designing voice agents to optimize both emotional engagement and practical functionality. Despite these insights, this study has several limitations that suggest potential directions for further investigation. The participant sample, consisting of young, healthy students, lacked diversity in age, gender, and driving experience, which may limit the generalizability of our findings. Additionally, the small sample size of 30 participants may affect the robustness of the results. Future studies should aim for a larger and more diverse participant pool to enhance the applicability of the findings across different demographic groups. Furthermore, the experimental setup was conducted in a controlled laboratory environment, which does not fully replicate real-world driving conditions. Environmental factors such as noise and the presence of other passengers were not considered, which could influence the effectiveness of voice interactions. Future research should explore these interactions in more naturalistic settings, including real vehicle experiments, to validate and expand upon our findings. In addition, the combination of mechanical voices with highly emotional or humanized agents was not explored in the present study. Investigating how users respond to emotionally expressive agents with mechanical voices remains an untested area and could provide valuable insights into the balance between functionality and emotional engagement. Future research should consider exploring this combination across different interaction contexts, such as customer service or safety-critical scenarios, to further understand the role of voice characteristics in shaping the UX. Finally, this study focused on a single, generic driving scenario. Future studies should investigate a wider range of driving contexts, such as highways and country roads, and various tasks, including emergency handling and entertainment system control, to provide a more comprehensive understanding of user interactions with voice agents in autonomous vehicles. Additionally, further exploration could be conducted on user preferences for different types of voice assistants and the psychological and emotional factors influencing these preferences. Conceptualization, Y.M.K. and J.K.; Funding acquisition, D.P. ; Methodology, Y.M.K. and D.P. ; Project administration, Y.M.K. ; Supervision, D.P. ; Writing--original draft, Y.M.K. and D.P. ; Writing--review & editing, J.K. All authors have read and agreed to the published version of the manuscript. This research was also partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2023-00242528).