4bc53a7f6c
* pr agent behaviors * pr agent behaviors * Add files via upload * Add files via upload * Add files via upload * Add files via upload * limits for steering * Add files via upload * pylint formatting * pylint formatting * seed flag for repeatability * seed flag for repeatability * Add files via upload * Add files via upload * first pr review corrections * Add files via upload * Add files via upload * Delete parameters.py * Add files via upload * Add files via upload * Add files via upload * Add files via upload * start of pedestrian avoidance + minor fixes * start of pedestrian avoidance + minor fixes * get_map check * get_map check * get_map check. * Delete basic_agent.py * Delete roaming_agent.py * pylint final changes * Pylint final check * more pylint * minor fix * minor changes * Add files via upload * changes in PID + old models * trying to stabilize waypoint distance * fixed step in sampling radius * folder structure change and more stuff * pylint fix * re-introducing pedestrian avoidance * minor things * deleted unused folder * restore basic folder * resurrected behavior agent * set debug to false * remove prints + open PR * changelog * setting behavior agent as default in auto_control changing manual_control to have slower increasing braking too * Requested modifications PR The vehicle can now accelerate and brake at the same time again. Removed unnecessary variable. * Fix frame rate display for the client * removing unnecessary duplication reordering folders code cleanup for codacity * unused import * codacity and travis changes Co-authored-by: Joel Moriana <joel.moriana@gmail.com> |
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| Import | ||
| LibCarla | ||
| PythonAPI | ||
| Unreal/CarlaUE4 | ||
| Util | ||
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README.md
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.
If you want to benchmark your model in the same conditions as in our CoRL’17 paper, check out Benchmarking.
CARLA Ecosystem
Repositories associated to the CARLA simulation platform:
- Scenario_Runner: Engine to execute traffic scenarios in CARLA 0.9.X
- ROS-bridge: Interface to connect CARLA 0.9.X to ROS
- Driving-benchmarks: Benchmark tools for Autonomous Driving tasks
- Conditional Imitation-Learning: Training and testing Conditional Imitation Learning models in CARLA
- AutoWare AV stack: Bridge to connect AutoWare AV stack to CARLA
- Reinforcement-Learning: Code for running Conditional Reinforcement Learning models in CARLA
- Map Editor: Standalone GUI application to enhance RoadRunner maps with traffic lights and traffic signs information
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 = {2017}
}
Building CARLA
Use git clone or download the project from this page. Note that the master
branch contains the latest fixes and features, for the latest stable code may be
best to switch to the stable branch.
Then follow the instruction at How to build on Linux or How to build on Windows.
Unfortunately we don't have official instructions to build on Mac yet, please check the progress at issue #150.
Contributing
Please take a look at our Contribution guidelines.
F.A.Q.
If you run into problems, check our FAQ.
License
CARLA specific code is distributed under MIT License.
CARLA specific assets are distributed under CC-BY License.
The ad-rss-lib library compiled and linked by the RSS Integration build variant introduces LGPL-2.1-only License.
Note that UE4 itself follows its own license terms.