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carla-simulator/carla

Open-source simulator for autonomous driving research

GraphCanon updated 3w · GitHub synced 3w

14k stars4.6k forksLast push 1mo C++ MIT

Decision brief

CARLA is suitable for teams focusing on autonomous driving research with high-fidelity sensor data and environmental modeling needs.

Good fit when

  • When your project requires Unreal Engine 5.5 capabilities for realistic simulation of complex autonomous vehicle scenarios
  • If you have access to powerful hardware including Ubuntu 22.04, or Windows 11 operating system, as it supports these systems specifically

Avoid when

  • If your project or research does not require the advanced features of Unreal Engine 5.5 and you are constrained by older hardware or software like Windows 10 or Ubuntu 20.04
  • When your immediate focus is on rapid deployment rather than simulation, as setting up CARLA requires significant setup time due to its system requirements

Observed Jul 17, 2026 · Source: enrich:decision_facts

Verify the decision

Maintenance and security

Full trust report
Maintenance
Very active (4d since push)
As of 3w
Provenance
Not a fork · Organization account
As of 3w
Security (OSV)
6 low (6 low)
As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

git clone https://github.com/carla-simulator/carla

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

CARLA Simulator is an open-source platform specifically designed to support the development and testing of autonomous driving systems through flexible sensor suite specification and environmental condition settings.

Capability facts

Languages
c++

Source: github.language · Jul 31, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 31, 2026)

- [Python API reference](https://carla-ue5.readthedocs.io/en/latest/python_api/)
Source link

Tags

README

CARLA Simulator

CARLA is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites and environmental conditions.

[!NOTE] This is the development branch ue5-dev for the Unreal Engine 5.5 version of CARLA. This branch exists in parallel with the Unreal Engine 4.26 version of CARLA, in the ue4-dev branch. Please be sure that this version of CARLA is suitable for your needs as there are significant differences between the UE 5.5 and UE 4.26 versions of CARLA.

Recommended system

  • Intel i7 gen 9th - 11th / Intel i9 gen 9th - 11th / AMD Ryzen 7 / AMD Ryzen 9
  • +32 Gb RAM memory
  • NVIDIA RTX 3070/3080/3090 / NVIDIA RTX 4090 / NVIDIA RTX 5090 or better
  • 16 Gb or more VRAM
  • Ubuntu 22.04 or 24.04, or Windows 11

[!NOTE] You must use either Ubuntu 22.04 or 24.04, or Windows 11. The Unreal Engine 5.5 version of CARLA will not work on Ubuntu 20.04 or Windows 10 or lower.

Documentation

The CARLA documentation is hosted on ReadTheDocs. Please see the following key links:

CARLA Ecosystem

Repositories associated with the CARLA simulation platform:

Like what you see? Star us on GitHub to support the project!

Paper

If you use CARLA, please cite our CoRL’17 paper.

CARLA: An Open Urban Driving Simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, Vladlen Koltun; PMLR 78:1-16 [PDF] [talk]

@inproceedings{Dosovitskiy17,
  title = {{CARLA}: {An} Open Urban Driving Simulator},
  author = {Alexey Dosovitskiy and German Ros and Felipe Codevilla and Antonio Lopez and Vladlen Koltun},
  booktitle = {Proceedings of the 1st Annual Conference on Robot Learning},
  pages = {1--16},
  year

For agents

This page has a .md twin and JSON over the API.

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