{"data":{"slug":"carla-simulator-carla","name":"carla","tagline":"Open-source simulator for autonomous driving research","github_url":"https://github.com/carla-simulator/carla","owner":"carla-simulator","repo":"carla","owner_avatar_url":"https://avatars.githubusercontent.com/u/33029185?v=4","primary_language":"C++","stars":14412,"forks":4700,"topics":["ai","artificial-intelligence","autonomous-driving","autonomous-vehicles","carla","carla-simulator","computer-vision","cross-platform","deep-learning","deep-reinforcement-learning","imitation-learning","research","ros","self-driving-car","simulator","ue4","unreal-engine-4"],"archived":false,"github_pushed_at":"2026-09-18T18:07:34+00:00","maintenance_label":"Very active","stars_delta_30d":178,"url":"https://www.graphcanon.com/tools/carla-simulator-carla","markdown_url":"https://www.graphcanon.com/tools/carla-simulator-carla.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/carla-simulator-carla","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=carla-simulator-carla","description":"Open-source simulator for autonomous driving research.","homepage_url":"http://carla.org","license":"MIT","open_issues":1196,"watchers":265,"ai_summary":"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.","readme_excerpt":"CARLA Simulator\n===============\n\n\n\n\n\n\n\n\n\nCARLA is an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and\nvalidation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings,\nvehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites and\nenvironmental conditions.\n\n\n\n>[!NOTE]\n> 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. \n\n### Recommended system\n\n* Intel i7 gen 9th - 11th / Intel i9 gen 9th - 11th / AMD Ryzen 7 / AMD Ryzen 9\n* +32 Gb RAM memory \n* NVIDIA RTX 3070/3080/3090 / NVIDIA RTX 4090 / NVIDIA RTX 5090 or better\n* 16 Gb or more VRAM\n* Ubuntu 22.04 or 24.04, or Windows 11\n\n >[!NOTE]\n> 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.\n\n## Documentation\n\nThe [CARLA documentation](https://carla-ue5.readthedocs.io/en/latest/) is hosted on ReadTheDocs. Please see the following key links:\n\n- [Building on Linux](https://carla-ue5.readthedocs.io/en/latest/build_linux_ue5/)\n- [Building on Windows](https://carla-ue5.readthedocs.io/en/latest/build_windows_ue5/)\n- [First steps](https://carla-ue5.readthedocs.io/en/latest/tuto_first_steps/)\n- [CARLA asset catalogue](https://carla-ue5.readthedocs.io/en/latest/catalogue/)\n- [Python API reference](https://carla-ue5.readthedocs.io/en/latest/python_api/)\n- [Blueprint library](https://carla-ue5.readthedocs.io/en/latest/bp_library/)\n\n## CARLA Ecosystem\nRepositories associated with the CARLA simulation platform:\n\n* [**CARLA Autonomous Driving leaderboard**](https://leaderboard.carla.org/): Automatic platform to validate Autonomous Driving stacks\n* [**Scenario_Runner**](https://github.com/carla-simulator/scenario_runner): Engine to execute traffic scenarios in CARLA 0.9.X\n* [**ROS-bridge**](https://github.com/carla-simulator/ros-bridge): Interface to connect CARLA 0.9.X to ROS\n* [**Driving-benchmarks**](https://github.com/carla-simulator/driving-benchmarks): Benchmark tools for Autonomous Driving tasks\n* [**Conditional Imitation-Learning**](https://github.com/felipecode/coiltraine): Training and testing Conditional Imitation Learning models in CARLA\n* [**AutoWare AV stack**](https://github.com/carla-simulator/carla-autoware): Bridge to connect AutoWare AV stack to CARLA\n* [**Reinforcement-Learning**](https://github.com/carla-simulator/reinforcement-learning): Code for running Conditional Reinforcement Learning models in CARLA\n* [**RoadRunner**](https://www.mathworks.com/products/roadrunner.html): MATLAB GUI based application to create road networks in OpenDrive format \n* [**Map Editor**](https://github.com/carla-simulator/carla-map-editor): Standalone GUI application to enhance RoadRunner maps with traffic lights and traffic signs information\n\n\n**Like what you see? Star us on GitHub to support the project!**\n\nPaper\n-----\n\nIf you use CARLA, please cite our CoRL’17 paper.\n\n_CARLA: An Open Urban Driving Simulator_<br>Alexey Dosovitskiy, German Ros,\nFelipe Codevilla, Antonio Lopez, Vladlen Koltun; PMLR 78:1-16\n[[PDF](http://proceedings.mlr.press/v78/dosovitskiy17a/dosovitskiy17a.pdf)]\n[[talk](https://www.youtube.com/watch?v=xfyK03MEZ9Q&feature=youtu.be&t=2h44m30s)]\n\n\n```\n@inproceedings{Dosovitskiy17,\n  title = {{CARLA}: {An} Open Urban Driving Simulator},\n  author = {Alexey Dosovitskiy and German Ros and Felipe Codevilla and Antonio Lopez and Vladlen Koltun},\n  booktitle = {Proceedings of the 1st Annual Conference on Robot Learning},\n  pages = {1--16},\n  year","github_created_at":"2017-10-24T09:06:23+00:00","created_at":"2026-07-11T12:22:23.649579+00:00","updated_at":"2026-09-21T06:00:33.60356+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"artificial-intelligence","name":"artificial-intelligence"},{"slug":"autonomous-driving","name":"autonomous-driving"},{"slug":"computer-vision","name":"computer-vision"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"deep-reinforcement-learning","name":"deep-reinforcement-learning"},{"slug":"imitation-learning","name":"imitation-learning"},{"slug":"research","name":"research"}],"trust":{"provenance":{"is_fork":false,"github_id":108102826,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-21T06:00:32.502Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":2,"last_release_at":"2025-09-16T09:32:23Z","stars_delta_30d":178,"open_issues_delta_30d":13},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":6,"high_count":0,"last_scan_at":"2026-07-11T12:22:30.636Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-21T06:00:33.139Z"},"languages":{"value":["c++"],"source":"github.language","observed_at":"2026-09-21T06:00:33.139Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-21T06:00:33.139Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["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","For detailed environmental setting adjustments and versatile sensor suite specification during development stages"],"when_not_to_use":["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","If your project focuses on non-autonomous driving applications where the specialized assets and simulations of CARLA may not be directly applicable"],"source":"enrich:decision_facts","observed_at":"2026-07-17T13:05:39.083Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"CARLA is suitable for teams focusing on autonomous driving research with high-fidelity sensor data and environmental modeling needs."}]}}