AWS DeepRacer is an autonomous 1/18th scale race car designed to test reinforcement learning (RL) models by racing on a physical track. It provides a fully autonomous driving platform that enables developers to get hands-on experience with machine learning through a fun and engaging racing experience.
URL: Visit APIs.json URL
- Type: Index
- Position: Consuming
- Access: 3rd-Party
- Autonomous Vehicles, AWS, Machine Learning, Reinforcement Learning, Robotics
- Created: 2026-03-16
- Modified: 2026-04-19
The AWS DeepRacer API provides programmatic access to manage DeepRacer vehicles, reinforcement learning models, leaderboards, and racing tracks for autonomous racing experiences on AWS.
Human URL: https://aws.amazon.com/deepracer/
- Autonomous Racing, Machine Learning, Reinforcement Learning, Robotics, AWS
- Vehicle management — register, configure, and organize physical DeepRacer vehicles into fleets
- Reinforcement learning model management — list, inspect, and delete trained RL models
- Leaderboard participation — browse active leaderboards, review tracks, and monitor competitive rankings
- Submission tracking — view participant rankings, lap times, and average performance across evaluations
- Track discovery — browse available virtual racing tracks for training and evaluation
- ARN-based resource addressing — all DeepRacer resources are identified by AWS ARNs for consistent access control
- Reinforcement Learning Education — Provide developers hands-on RL experience through competitive autonomous racing with immediate feedback loops
- ML Model Iteration — Train, evaluate, and compare multiple reinforcement learning models against standardized racing tracks
- Corporate ML Training Events — Organize internal DeepRacer leagues with fleet management, custom leaderboards, and participant tracking
- Championship Qualification — Submit models to official AWS DeepRacer League leaderboards to qualify for global championship racing events
- Robotics Research — Use DeepRacer as an accessible physical platform for testing autonomous navigation algorithms
- Amazon SageMaker — Training platform that generates DeepRacer RL model artifacts referenced by the DeepRacer API
- Amazon S3 — Storage for model artifacts, reward function code, training logs, and simulation data
- AWS RoboMaker — Robotics simulation service used for virtual racing environments during RL model training
- Amazon CloudWatch — Monitoring for training metrics, model evaluation logs, and API usage statistics
- AWS IAM — Role-based access control for vehicle management, model operations, and leaderboard administration
| Type | URL |
|---|---|
| Portal | https://aws.amazon.com/deepracer/ |
| Website | https://aws.amazon.com/deepracer/ |
| Documentation | https://docs.aws.amazon.com/deepracer/ |
| TermsOfService | https://aws.amazon.com/service-terms/ |
| PrivacyPolicy | https://aws.amazon.com/privacy/ |
| Support | https://aws.amazon.com/premiumsupport/ |
| Blog | https://aws.amazon.com/blogs/machine-learning/tag/aws-deepracer/ |
| GitHubOrganization | https://github.com/aws |
| Console | https://console.aws.amazon.com/deepracer/ |
| SignUp | https://portal.aws.amazon.com/billing/signup |
| Login | https://signin.aws.amazon.com/ |
| StatusPage | https://health.aws.amazon.com/health/status |
| Contact | https://aws.amazon.com/contact-us/ |
FN: Kin Lane
Email: kin@apievangelist.com