This study proposes a Human-Machine Interface (HMI) implementation for autonomous vehicles aimed at ensuring the safety of vulnerable vehicle users, such as the elderly, disabled, and residents of transportation- disadvantaged areas. Particularly, sharp turn detection algorithm was developed to provide pre-emptive warnings to passengers about sudden vehicle movements, enhancing safety and comfort. Field tests conducted using high-definition map (HD map) of Sejong City demonstrated the effectiveness of the system, allowing autonomous vehicles to detect sharp turns in advance and display appropriate warning messages through the HMI. The results show that the proposed system improves the safety of vulnerable vehicle users by providing early detection of sharp turns, thus reducing potential risks during autonomous vehicle rides. This research highlights the importance of user-friendly and intuitive HMI systems for increasing public trust and acceptance of autonomous driving technologies, and it contributes to the development of a more inclusive and accessible transportation system. The findings are expected to play a key role in advancing the commercialization and widespread adoption of autonomous vehicles for all users.