Off the Beaten Sidewalk: Pedestrian Prediction in Shared Spaces for Autonomous Vehicles

@article{Anderson2020OffTB,
  title={Off the Beaten Sidewalk: Pedestrian Prediction in Shared Spaces for Autonomous Vehicles},
  author={Cyrus Anderson and Ram Vasudevan and Matthew Johnson-Roberson},
  journal={IEEE Robotics and Automation Letters},
  year={2020},
  volume={5},
  pages={6892-6899}
}
Pedestrians and drivers interact closely in a wide range of environments. Autonomous vehicles (AVs) correspondingly face the need to predict pedestrians’ future trajectories in these same environments. Traditional model-based prediction methods have been limited to making predictions in highly structured scenes with signalized intersections, marked crosswalks, or curbs. Deep learning methods have instead leveraged datasets to learn predictive features that generalize across scenes, at the cost… 

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