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Targeted Adversarial Attacks Against Neural Network Trajectory Predictors, Kaiyuan Tan
Targeted Adversarial Attacks Against Neural Network Trajectory Predictors, Kaiyuan Tan
McKelvey School of Engineering Theses & Dissertations
Trajectory prediction is an integral component of modern autonomous systems as it allows for envisioning future intentions of nearby moving agents. Due to the lack of other agents' dynamics and control policies, deep neural network (DNN) models are often employed for trajectory forecasting tasks. Although there exists an extensive literature on improving the accuracy of these models, there is a very limited number of works studying their robustness against adversarially crafted input trajectories. To bridge this gap, in this paper, we propose a targeted adversarial attack against DNN models for trajectory forecasting tasks. We call the proposed attack TA4TP for …