pangjinlongpjl / eudm_planner

Implementation of the paper "Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching".

EUDM Planner

• Update (Sept. 2020): The whole dependencies and a playable demo will be released in: https://github.com/HKUST-Aerial-Robotics/EPSILON

• Notice: The current version is for reference only.

Introduction

This is the project page of the paper "Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching" which is accepted by IEEE International Conference on Robotics and Automation (ICRA) 2020.

Our paper is currently available on arXiv.

• Lu Zhang, Wenchao Ding, Jing Chen and Shaojie Shen. Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching. arXiv preprint arXiv:2003.02746.

• L. Zhang and W. Ding contributed equally to this project.

@article{zhang2020efficient,
  title={Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching},
  author={Zhang, Lu and Ding, Wenchao and Chen, Jing and Shen, Shaojie},
  journal={arXiv preprint arXiv:2003.02746},
  year={2019}
}

Videos:

The overall structure is shown as follows: