Metamorphic Testing of Multimodal Human Trajectory Prediction

Helge Spieker, Arnaud Gotlieb, Nadjib Lazaar, Nassim Belmecheri

Abstract: Predicting human trajectories is crucial for the safety and reliability of autonomous systems, such as automated vehicles and mobile robots. However, rigorously testing the underlying multimodal Human Trajectory Prediction (HTP) models, which typically use multiple input sources (e.g., trajectory history and environment maps) and produce stochastic outputs (multiple possible future paths), presents significant challenges. The primary difficulty lies in the absence of a definitive test oracle, as numerous future trajectories might be plausible for any given scenario.