How does adversarial training impact the robustness of multimodal trajectory prediction models against perturb

Abstract

Abstract: Predicting the trajectories of surrounding objects is a critical task for self-driving vehicles and many other autonomous systems. Recent works demonstrate that adversarial attacks on trajectory prediction, where small crafted perturbations are introduced to history trajectories, may significantly mislead the prediction of future trajectories and induce unsafe planning. However, few works have addressed enhancing the robustness of this important safety-critical task.In this paper, we present a novel adversarial training method for trajectory prediction. Compared with typical adversarial traini

Research Question

How does adversarial training impact the robustness of multimodal trajectory prediction models against perturbations in visual input modalities?

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