AlpaSim: A modular, lightweight, and data-driven research simulator for autonomous driving

What is AlpaSim?

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

Sensor Fidelity

• Neural Rendering (NuRec) integration for photorealistic sensor simulation of novel views

• High-fidelity camera feeds with configurable field-of-view, resolution, and frame rates

• Realistic sensor noise and environmental conditions

Research Hackability

• 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

Horizontal Scalability

• 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.

Driving Policies

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.

Getting Started

To run simulations locally (Docker Compose, single machine), see the Tutorial. For cluster or SLURM deployment, see src/tools/run-on-slurm.

Documentation & Resources

• Onboarding Guide: Initial setup and access instructions

• Tutorial: Step-by-step usage guide

• Manual Driver: Interactive keyboard control of the ego vehicle

• Operations Guide: Performance tuning, configuration, and troubleshooting

• 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

Sample Data

• Hugging Face Dataset: PhysicalAI-Autonomous-Vehicles-NuRec

• Sample Artifacts: Included in the repository via Git LFS

Contributing

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

License

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

Citation

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},
}

Project Contributors:

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