The successful deployment of autonomous vehicles (AVs) relies heavily on their ability to interact safely and effectively with other road users. External human–machine interfaces (eHMIs) have emerged as critical components in facilitating these interactions. Rigorous evaluation and testing of eHMIs are essential for realizing their intended safety and communication benefits. This study provides a comprehensive review of current eHMI research, focusing on their impact on road users’ behavior and perceptions, as well as the methods used for evaluation. Key behavioral factors—such as eHMI modality, information type, location, vehicle kinematics, traffic environment, and user characteristics—are systematically reviewed and summarized. The influence of eHMIs on user perceptions is also explored through indicators such as perceived safety, comprehensibility, trust, cognitive load, and user experience. Despite notable advancements, several critical research gaps remain underexplored. Most studies focus on one-to-one interactions, neglecting the complexities of mixed-traffic environments involving AVs, conventional human-driven vehicles, pedestrians, and cyclists. Current evaluation methods largely rely on virtual reality and Wizard-of-Oz experiments, which may fail to fully capture real-world dynamics. Additionally, subjective questionnaires, which are often used in these studies, do not guarantee high reproducibility of findings. Moreover, insufficient attention has been given to the synchronization of eHMI signals with vehicle kinematics. Furthermore, the absence of standardized evaluation frameworks limits cross-study comparability and the development of universally applicable eHMI solutions. To address these challenges, future research should prioritize the integration of naturalistic traffic scenarios, the adoption of objective and reproducible evaluation methods, the exploration of multimodal eHMI designs, and the development of standardized assessment protocols. These efforts are crucial for improving AV communication with diverse road users and ensuring safety in increasingly complex traffic ecosystems.