Deep neural networks for Markovian interactive scene prediction in highway scenarios

@article{Lenz2017DeepNN,
  title={Deep neural networks for Markovian interactive scene prediction in highway scenarios},
  author={David Lenz and Frederik Diehl and Michael Truong-Le and Alois Knoll},
  journal={2017 IEEE Intelligent Vehicles Symposium (IV)},
  year={2017},
  pages={685-692}
}
In this paper, we compare different deep neural network approaches for motion prediction within a highway entrance scenario. The focus of our work lies on models that operate on limited history of data in order to fulfill the Markov property1 and be usable within an integrated prediction and motion planning framework for automated vehicles. We examine different model structures and feature combinations in order to find a model with a good tradeoff between accuracy and computational performance… CONTINUE READING
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