Pedestrian trajectory prediction using goal-driven and dynamics-based deep learning framework

Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra

Abstract: Highlights•Prediction of pedestrian trajectory can be vital in avoiding road accidents.•We present a dynamical system within a deep learning-based framework.•We use the Transformer model with the dynamical system for prediction.•Our framework outperforms related models on benchmark datasets.•We provide insights into the different categories of pedestrian trajectories.

External IDs:dblp:journals/eswa/WangZBC25