Acknowledgement

Note

The VISTA simulator is a result of many contributions across many different individuals. The project has been led by Alexander Amini, Tsun-Hsuan (Johnson) Wang, and Daniela Rus.

We acknowledge contributions from authors (alphabetically): Alexander Amini, Rohan Banerjee, Igor Gilitschenski, Song Han, Sertac Karaman, Zhijian Liu, Julia Moseyko, Jacob Phillips, Daniela Rus, Wilko Schwarting, Tsun-Hsuan (Johnson) Wang.

We also acknowledge funding support from the National Science Foundation (NSF), Toyota Research Institute (TRI), and NVIDIA.

Citing VISTA

If VISTA is useful or relevant to your research, we ask that you recognize our contributions by citing the following three original VISTA papers in your research:

VISTA 1.0: Sim-to-real RL

@article{amini2020learning,
    title={Learning Robust Control Policies for End-to-End Autonomous Driving from Data-Driven Simulation},
    author={Amini, Alexander and Gilitschenski, Igor and Phillips, Jacob and Moseyko, Julia and Banerjee, Rohan and Karaman, Sertac and Rus, Daniela},
    journal={IEEE Robotics and Automation Letters},
    year={2020},
    publisher={IEEE}
}

VISTA 2.0: Multi-sensor

@inproceedings{amini2022vista,
  title={VISTA 2.0: An Open, Data-driven Simulator for Multimodal Sensing and Policy Learning for Autonomous Vehicles},
  author={Amini, Alexander and Wang, Tsun-Hsuan and Gilitschenski, Igor and Schwarting, Wilko and Liu, Zhijian and Han, Song and Karaman, Sertac and Rus, Daniela},
  booktitle={2022 International Conference on Robotics and Automation (ICRA)},
  year={2022},
  organization={IEEE}
}

VISTA 2.0: Multi-agent

@inproceedings{wang2022learning,
  title={Learning Interactive Driving Policies via Data-driven Simulation},
  author={Wang, Tsun-Hsuan and Amini, Alexander and Schwarting, Wilko and Gilitschenski, Igor and Karaman, Sertac and Rus, Daniela},
  booktitle={2022 International Conference on Robotics and Automation (ICRA)},
  year={2022},
  organization={IEEE}
}

Contribution Guidelines

VISTA is constantly being advanced and has been built with research, extensibility, and community development as a priority. We actively encourage contributions to the VISTA repository and codebase, including issues, enhancements, and pull requests.