<p>Human trajectory prediction has garnered significant attention due to its critical role in applications such as autonomous vehicles, service robots, and advanced surveillance systems. As this research area evolves rapidly, numerous research centers are initiating projects dedicated to this domain. In this survey, we provide a comprehensive review of existing methods for human trajectory prediction, emphasizing the key challenges and outlining future research directions. We review a broad range of existing studies and propose a taxonomy that categorizes these methods based on their motion modeling approaches, output types, and situational awareness (including interactions and contextual information). We also discuss the datasets commonly used and the performance metrics applied in this field. Additionally, we address the limitations of current state-of-the-art techniques and offer suggestions for future research.</p>