Coming soon!
This is the reference implementation for our paper:
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation PDF
Matthew O'Kelly*, Aman Sinha*, Hongseok Namkoong*, John Duchi, Russ Tedrake
Abstract: While recent developments in autonomous vehicle technology highlight substantial progress, we lack tools for rigorous and scalable testing. Real-world testing, the de facto evaluation environment, places the public in danger, and, due to the rare nature of accidents, will require billions of miles in order to statistically validate performance claims. We implement a simulation framework that can test an entire modern autonomous driving system, including, in particular, systems that employ deep-learning based perception and control algorithms. Using adaptive importance-sampling methods to accelerate rare-event probability evaluation, we estimate the probability of an accident under a base distribution (learned from real-world data) governing standard traffic behavior. We demonstrate our framework on a highway scenario, our evaluation is 2-20 faster than naive Monte Carlo sampling methods and 10-300 times (where P is the number of processors) faster than real-world testing.
If you find this code useful in your work, please consider citing:
@inproceedings{okelly2018,
title={Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation},
author={O'Kelly*, Matthew and Sinha*, Aman and Namkoong*, Hongseok and Tedrake, Russ and Duchi, John},
booktitle={Advances in Neural Information Processing Systems},
year={2018}
}
Requires:
- docker
- nvidia-docker2
- A recent Nvidia GPU e.g. GTX980 or better.
The docker image essentially packages all dependencies in a safe environment. The scripts we provide will externally mount our source code, and our models, into the docker environment.
Most source code for this project is in Python and so once the docker image is built we won't need any compiling.
The following is all of the steps to build a docker image for RareSim
from a fresh Ubuntu installation:
- Install Docker for Ubuntu. Make sure to
sudo usermod -aG docker your-user
and then not run below docker scripts assudo
- Install
nvidia-docker
. Make sure to usenvidia-docker2
notnvidia-docker1
.
sudo apt-get install -y nvidia-docker2
You can test that your nvidia-docker installation is working by running
nvidia-docker run --rm nvidia/cuda nvidia-smi
If you get errors about nvidia-modprobe not being installed, install it by running
sudo apt-get install nvidia-modprobe
and then restart your machine.
Coming soon