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
- 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
- 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.
- Onboarding Guide: Initial setup and access instructions
- Tutorial: Step-by-step usage guide
- Operations Guide: Performance tuning, configuration, and troubleshooting
- Design Documentation: Technical architecture and design decisions
- API Reference: gRPC API documentation
- Hugging Face Dataset: PhysicalAI-Autonomous-Vehicles-NuRec
- 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
Accelerating autonomous vehicle development through realistic simulation