Training self-driving cars on the streets of Los Santos with GTA V just got lighter
The DeepDrive project has made it possible to use Grand Theft Auto to train self-driving cars for some time now. But today, the work is being integrated and open-sourced with OpenAI’s Universe. The collaboration will cut the once day-long setup time down to just twenty minutes.
Training AI frameworks on synthetic data is all the rage these days. Large tech companies and startups alike are digging around for nifty training methods that can reduce the barriers to getting in the self-driving car game and make annotations less of a ache. Companies like Udacity have been steadily releasing real-world driving data, but community needs to proceed to grow in volume and specificity.
OpenAI’s Universe came about late last year to address some of this market need, launching with Atari two thousand six hundred games, 1,000 flash games and eighty browser environments to help democratize access to training resources. The addition of GTA V is a significant improvement over racing Flash games and opens the door to computer vision and autonomous car researchers.
“Simulation is essential if you truly want to do a self driving car,” said Zhaoyin Jia, tech lead for Google self driving at today’s AI Frontiers Conference.
While I can’t say I would want any self-driving car being trained based on my GTA V driving, the game is realistic enough for slightly more disciplined individuals to get the job done.
One of the thickest advantages of training off of a virtual environment is that its primed for harvesting labeled data. Objects in GTA V, whether traffic signs or cyclists, can lightly be bounded and analyzed.
One Princeton student, Artur Filipowicz, specifically made use of this to collect 1.Four million pics of stop signs in a multiplicity of conditions to predict the chance a given intersection will have a sign present and to estimate the distance to the given sign.
Pulled from research entitled “Driving School II, Movie Games for Autonomous Driving” ended by Artur Filipowicz of Princeton University
Commencing today, those with a penchant for DIY training can obtain the source code and AMI for GTA V and nab a pre-trained starter agent with TensorFlow and Caffe versions. The kit also includes prize functions for collision avoidance, minimizing destination distance, and maximizing adherence to the road. By putting things in terms of utility, computers can better emulate human thinking with reinforcement learning.
The team is running the game off of a Windows virtual machine hosted in the cloud that communicates with Universe via web sockets and VNC. That provides accessibility to engineers on both Mac and Linux. Oh, and don’t leave behind, before you get commenced you’ll need to buy yourself a copy of the game too.
Featured Picture: LEON NEAL/AFP/Getty Photos