[8] DYNAMIC TRAJECTORY FORECASTING IN CROWDED SPACES: AN IN-DEPTH REVIEW OF ONLINE AND ADAPTIVE PREDICTION METHODS

ARTICLE HISTORY- Date of Submission: Oct 08, 2024, Revised: Oct 23, 2024, Accepted: Nov 02, 2024, https://doi.org/10.56815/IJMRR.V3I4.2024/87-102

Abstract

As they navigate city streets, autonomous cars will unavoidably collide with people. Research on pedestrian trajectory prediction is crucial for preventing route conflicts with pedestrians. This study summarizes the current public dataset for pedestrian trajectory prediction and compares the performance of various methods. It also examines the pros and cons of depth learning-based trajectory prediction methods. In conclusion, we look forward to the current state of pedestrian trajectory prediction and the difficulties and trends in its growth.