Evaluating Pedestrian Trajectory Prediction Methods with Respect to Autonomous Driving

arXiv:2308.05194v3 Announce Type: replace
Abstract: In this paper, we assess the state of the art in pedestrian trajectory prediction within the context of generating single trajectories, a critical aspect aligning with the requirements in autonomous systems. The evaluation is conducted on the widely-used ETH/UCY dataset where the Average Displacement Error (ADE) and the Final Displacement Error (FDE) are reported. Alongside this, we perform an ablation study to investigate the impact of the observed motion history on prediction performance. To evaluate …

abstract art arxiv autonomous autonomous driving autonomous systems context cs.lg cs.ro dataset driving error eth evaluation paper pedestrian prediction requirements state state of the art systems trajectory type