Self-Supervised Action-Space Prediction for Automated Driving

@article{Janjos2021SelfSupervisedAP,
  title={Self-Supervised Action-Space Prediction for Automated Driving},
  author={Faris Janjos and Maxim Dolgov and Johann Marius Z{\"o}llner},
  journal={2021 IEEE Intelligent Vehicles Symposium (IV)},
  year={2021},
  pages={200-207}
}
Making informed driving decisions requires reliable prediction of other vehicles' trajectories. In this paper, we present a novel learned multi-modal trajectory prediction architecture for automated driving. It achieves kinematically feasible predictions by casting the learning problem into the space of accelerations and steering angles - by performing action-space prediction, we can leverage valuable model knowledge. Additionally, the dimensionality of the action manifold is lower than that of… 

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