AWS DeepRacer FAQs

Q: What is AWS DeepRacer?
AWS DeepRacer is the fastest way to get rolling with reinforcement learning (RL), literally, with a fully autonomous 1/18th scale race car driven by reinforcement learning and 3D racing simulator. Anyone can can train, evaluate, and tune RL models in the online simulator, deploy models onto an AWS DeepRacer device for a real-world autonomous experience or compete in console against each other.  AWS DeepRacer Device Terms, Warranties, and Notices »

Q: What is the AWS DeepRacer League?
The AWS DeepRacer League was the world’s first global autonomous racing league. Since 2018, more than 560,000 builders have grown their knowledge of machine learning (ML) by competing in the League, with the best of the best convening every year at re:Invent in Las Vegas for the AWS DeepRacer League Championship. 

You can read more about the final Championship on the DeepRacer Home page. 

Q: How do I get started with AWS DeepRacer simulator?
The AWS DeepRacer simulator provides a tutorial to get you started with reinforcement learning and training your first model. You will then also be able to evaluate and tune your models. The AWS DeepRacer Developer Documentation provides additional details on building your first model and also how to improve your models.

Q: How can I start my own Community Race?
Customers can create their own virtual races the Community Races section of the AWS DeepRacer console.

Q: Do I need an AWS DeepRacer car in order to use the AWS DeepRacer simulator?
No. You can train models, evaluate them without owning an AWS DeepRacer car. 

Q: Does my DeepRacer device need to be connected to the internet to race autonomously?
No. AWS DeepRacer uses the deployed RL model and input from the camera to run inference locally. AWS DeepRacer must be connected to the same Wi-Fi network as the device used to start and stop autonomous driving. Details on how to set up your vehicle can be found in the Developer Documentation.

Q: What is AWS DeepRacer Student?
AWS DeepRacer Student lets high school and college-enrolled students around the globe develop their ML skills in a fun, hands-on way exclusively for students with no AWS account required. Participants can leverage 20 hours of ML educational material, 10 hours of monthly model training compute resources, and 5 GB of model storage to train a RL model in a simulated 3D racing environment. 

Q: Where can I find more details regarding AWS DeepRacer Student?
Go to AWS DeepRacer Student for more details. 

Q: Which AWS services are integrated with AWS DeepRacer?
AWS DeepRacer integrates with Amazon SageMaker for reinforcement learning model training, AWS RoboMaker to provide the racing simulator, Amazon Kinesis Video Streams for video streaming of virtual simulation footage, Amazon S3 for model storage, and Amazon CloudWatch for log capture.

Q: How do I add new tracks to the AWS DeepRacer simulator?
Currently, developers cannot add additional tracks to the AWS DeepRacer simulator. 

Q: Can I train my models on the AWS DeepRacer device?
No. Training an RL model requires feedback regarding the outcome of actions taken by the model. This feedback loop exists in the AWS DeepRacer simulator, but not in the real-world.

Q: Can I train my models locally on my own machine as opposed to the AWS Cloud?
Currently AWS DeepRacer does not support local training.

Q: Can I train AWS DeepRacer RL models directly on Amazon SageMaker?
Yes. You can use the AWS DeepRacer Distributed Training SageMaker Notebook to create and train RL models. You will be able to deploy these models to your AWS DeepRacer manually, but won’t yet be able to import them into the AWS DeepRacer console.