AlpaSim is an open-source autonomous vehicle simulation platform designed specifically for research and development. It allows users to test end-to-end AV policies in a closed-loop setting by simulating realistic sensor data, vehicle dynamics, and traffic scenarios within a modular and extensible testbed.

Suitable use cases include:

• Algorithm Validation: Test new autonomous driving algorithms in realistic environments
• Safety Analysis: Evaluate vehicle behavior in edge cases and challenging scenarios
• Performance Benchmarking/Regression Testing: Compare different models and configurations
• Debugging: Understand and debug complex autonomous driving behaviors

• Pluggable renderer service with default NuRec support and OmniDreams video-model rendering through FlashDreams
• High-fidelity camera feeds with configurable field-of-view, resolution, and frame rates
• Stateful video-model rendering for stronger dynamic-object and non-rigid visual fidelity
• Realistic sensor noise and environmental conditions

• Python-based implementation built for rapid prototyping and experimentation
• Modular grpc interface design allows researchers to swap out components with custom implementations
• Extensive configuration options and debugging tools

• Microservices architecture enabling distributed computing
• Scale individual components for optimal load balancing
• Support for multi-node deployments

To learn more about the design principles and architecture, check out the system design docs.

AlpaSim currently supports the following driver policies:

• Alpamayo-R1 - NVIDIA Alpamayo, a VLA driving policy with chain-of-causation reasoning
• Alpamayo 1.5 - Public Alpamayo 1.5 checkpoint support is also available
• VaVAM - an autoregressive video-action driving policy
• Transfuser - Latent TransFuser v6 (LTFv6) policy developed for NAVSIM (provisional)

Stay tuned for additional model support. Contributions from the community are appreciated.

📣 Usage questions and discussion about AlpaSim: please join us on the Alpamayo NV Developer Forum.

🐛 Code-level bugs, documentation issues, and feature requests: file a GitHub issue using the appropriate template (Bug report, Documentation request, or Feature request). The relevant NVIDIA responder is auto-assigned via the assignees: field on the template.

🚨 Security vulnerabilities: please use NVIDIA's Vulnerability Disclosure Program. Do not file security issues publicly here.

To run simulations locally (Docker Compose, single machine), see the Tutorial. The default tutorial path uses NuRec; for OmniDreams as the renderer backend, see the Video Model Renderer guide. For cluster or SLURM deployment, see src/tools/run-on-slurm.

• Onboarding Guide: Initial setup and access instructions
• Tutorial: Step-by-step usage guide
• Manual Driver: Interactive keyboard control of the ego vehicle
• Video Model Renderer: Running OmniDreams through FlashDreams as the AlpaSim renderer backend
• Operations Guide: Performance tuning, configuration, and troubleshooting
• Telemetry Guide: Prometheus metrics, persistence, and central discovery
• Data Pipeline: ASL log format and reading logs
• Design Documentation: Technical architecture and design decisions
• Plugin System: Extending AlpaSim with custom models, configs, and tools
• API Reference: gRPC API documentation
• Changelog: Major updates and migration notes
• Contributing: Code style, coordinate conventions, and PR process
• Developer Quick Reference: Build commands, testing, and CI workflow
• Test Suites & Scenes: Available scene datasets

• Hugging Face Dataset: PhysicalAI-Autonomous-Vehicles-NuRec 26.01 is recommended for new runs. See Test Suites & Scenes for release selection and legacy dataset commands.
• Sample Artifacts: Included in the repository via Git LFS

We welcome contributions from the research community! Please see our Contributing Guide for details on:

• Code style and conventions
• Testing requirements
• Pull request process
• Development setup

This project is licensed under the Apache License 2.0. See the LICENSE file for details.

If you use this software, please cite it as follows:

@software{alpasim_2025,
  author       = {
    NVIDIA and
    Yulong Cao and
    Riccardo de Lutio and
    Sanja Fidler and
    Guillermo Garcia Cobo and
    Zan Gojcic and
    Maximilian Igl and
    Boris Ivanovic and
    Peter Karkus and
    Janick Martinez Esturo and
    Marco Pavone and
    Aaron Smith and
    Ellie Tanimura and
    Michal Tyszkiewicz and
    Michael Watson and
    Qi Wu and
    Le Zhang
  },
  title        = {AlpaSim: A Modular, Lightweight, and Data-Driven Research Simulator for Autonomous Driving},
  year         = {2025},
  month        = {October},
  url          = {https://github.com/NVlabs/alpasim},
}

Contributors in each topic in alphabetical order

Project Lead: Maximilian Igl

Tech Leads: Michal Tyszkiewicz, Michael Watson

Architecture Design & Networking: Michal Tyszkiewicz

Open Sourcing: Guillermo Garcia Cobo, Maximilian Igl, Peter Karkus, Ellie Tanimura, Michael Watson

Infrastructure & Wizard: Maximilian Igl, Aaron Smith, Michal Tyszkiewicz, Michael Watson, Qi Wu (SLURM deployment), Le Zhang (Data management)

Runtime: Maximilian Igl, Aaron Smith, Ellie Tanimura, Michal Tyszkiewicz, Michael Watson

CICD: Maximilian Igl, Aaron Smith

Data Pipeline: Riccardo de Lutio, Janick Martinez, Le Zhang

Product Manager: Matt Cragun

Testing & debugging: Guillermo Garcia Cobo, Peter Karkus, Ellie Tanimura

Service Modules:

• Driver integration: Maximilian Igl, Peter Karkus, Michal Tyszkiewicz
• Evaluation: Yulong Cao, Maximilian Igl
• Controller: Michael Watson
• Physics: Riccardo de Lutio
• Trafficsim: Maximilian Igl, Boris Ivanovic

Senior Mgmt: Sanja Fidler, Zan Gojcic, Boris Ivanovic, Marco Pavone

Acknowledgements for additional contributions: Fabian Barajas, Kashyap Chitta, Ankit Gupta, Laura Leal-Taixe, Nicole Yang