self-driving AI

Deepdrive is an open simulation platform built to accelerate progress and increase transparency in self-driving AI. We enable more people to develop AI by decoupling it from self-driving hardware and facilitate research through establishing standard benchmarks and baselines.

Deepdrive 2.0

The easiest way to experiment with self-driving AI


Baseline agent
Use our pretrained example agent, training code, and dataset to get started building your own AI and try to beat our high score!
Download the 100GB, 8.2 hour, dataset we used to train the baseline agent, complete with depth, DAgger labels, and capture augmentation used to achieve scores on-par with the path-follower.
Modifiable source
Our AI, Unreal plugin, simulation assets and code, and Unreal Engine are all on GitHub, so you can modify the agent and the environment to automate labeling and iterate on ideas in minutes instead of weeks or months.
Eight cameras with depth
Enable up to eight cameras with images and depth transferred at blazing speeds via shared memory. i.e. Eight 512x512 48 bit RGB with 16 bit depth channel cameras, uncompressed on a GTX 980 over PCIe 3.0 x 16 are available at 20Hz as NumPy arrays.
Linux / Windows support
First class support for Linux and Windows, one command python, and you'll be piloting Deepdrive in minutes.
Visual scripting
Quickly change anything in the simulation with Unreal Blueprints, using the full power of Unreal's C++ API.
C++ extendability
Everything is C++ under the hood, so you can integrate existing systems and highly optimize anything you want.
Python API
Interface through the Gym API using a reward function based on speed, safety, legality, and comfort.
Example forward agent
import deepdrive as dd

def main():
    env = dd.start()
    forward = dd.action(throttle=1, steering=0, brake=0)
    done = False
    while not done:
        observation, reward, done, info = env.step(forward)

if __name__ == '__main__':


Deepdrive - Agents, training, and API to simulator - start here!
Deepdrive sim - Unreal project, Unreal Plugin, assets, and Python extension


Answers to common questions


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