Demonstration of Safe Area Estimation by Trajectory Prediction Using Nonparametric Bayesian Inverse Reinforcement Learning

Exhibition event

  • Automotive World 2020 (January 2020)


  • Estimation of safe area using trajectory prediction of other vehicles in an intersection scene.
  • Inverse reinforcement learning is used to predict the trajectories of other vehicles and humans.
    By using a nonparametric bayesian-based algorithm as an elemental technology, the following advantages can be realized.

    • Predictions close to human senses are possible
    • Requires less training data than conventional DeepLearning or probabilistic models
    • Can be processed by edge devices
    • Possible to analyze what is used to output inference results
    • No need for humans to provide parameters; the model itself makes the decision


  • Algorithm: ddBNIRL
  • Edge device: NVIDIA Jetson AGX Xavier
  • Green: Trajectory prediction results for other vehicles

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