PORCA: Modeling and planning for autonomous driving among many pedestrians.

This projects investigates a planning system for autonomous driving among many pedestrians. A key ingredient of our approach is a motion prediction model for pedestrians and vehicles. It accounts for both a pedestrian’s global navigation intention and local interactions with the vehicle and other pedestrians. Unfortunately, the autonomous vehicle does not know the pedestrians’ intentions a priori and requires a planning algorithm that hedges against the uncertainty in pedestrian intentions. Our planning system combines a POMDP algorithm with the pedestrian motion model and runs in real time. Experiments show that it enables a robot scooter to drive safely, efficiently, and smoothly in a crowd with a density of nearly one person per square meter.

@article{Luo2018PORCAMA,
  title={PORCA: Modeling and Planning for Autonomous Driving Among Many Pedestrians},
  author={Yuanfu Luo and Panpan Cai and Aniket Bera and David Hsu and Wee Sun Lee and Dinesh Manocha},
  journal={IEEE Robotics and Automation Letters},
  year={2018},
  volume={3},
  pages={3418-3425}
}
}