CARLA

!!! important This document refers to the latest version of CARLA built with Unreal Engine 5. For documentation relating to the Unreal Engine 4 version of CARLA please visit the documentation for this version.

CARLA is an open-source driving simulator for use in autonomous driving applications. It was built from scratch with a modular and flexible API to address a range of tasks involved in the problem of autonomous driving. One of the main goals of CARLA is to help democratize autonomous driving R&D, serving as a tool that can be easily accessed and customized by users. To do so, the simulator has to meet the requirements of different use cases within the general problem of driving (e.g. learning driving policies, training perception algorithms, etc.). CARLA is grounded on Unreal Engine to run the simulation and uses the OpenDRIVE standard (1.4 as today) to define roads and urban settings. Control over the simulation is granted through an API handled in Python and C++ that is constantly growing as the project does.

In order to smooth the process of developing, training and validating driving systems, CARLA evolved to become an ecosystem of projects, built around the main platform by the community. In this context, it is important to understand some things about how CARLA works, so as to fully comprehend its capabilities.

The simulator

The CARLA simulator consists of a scalable client-server architecture. The server is responsible for everything related to the simulation itself: sensor rendering, computation of physics, updates on the world-state and its actors and much more. Since CARLA requires significant graphical computing resources, it is necessary to use a dedicated, high-performance GPU.

The client side consists of a set of client modules controlling the behavior of actors and the state of the environment within the simulation. This is achieved by leveraging the CARLA API (in Python or C++), a layer that mediates between server and client that is constantly evolving to provide new functionalities.

The CARLA simulator combines a number of different features that handle different important aspects of the driving simulation. The following is a summary of some of the key modules:

Traffic manager: A built-in system that takes control of the vehicles besides the one used for learning. It acts as a conductor provided by CARLA to recreate urban-like environments with realistic behaviours.
Sensors :Vehicles rely on them to dispense information of their surroundings. In CARLA they are a specific kind of actor attached the vehicle and the data they receive can be retrieved and stored to ease the process. Currently the project supports different types of these, from cameras to radars, lidar and many more.
Recorder: The recorder can replay a simulation exactly to enable retrospective evaluation of the outcome of a simulation and to rerun the simulation with alternative configurations of sensors, for example.
ROS2: CARLA natively supports connectivity with ROS2, a widely used set of software libraries and tools for robotics and autonomous driving.
Open assets: CARLA facilitates different maps for urban settings with control over weather conditions and a blueprint library with a wide set of actors to be used. However, these elements can be customized and new can be generated following simple guidelines.
Scenario runner: In order to ease the learning process for vehicles, CARLA provides a series of routes describing different situations to iterate on. These also set the basis for the CARLA challenge, open for everybody to test their solutions and make it to the leaderboard.

The project

CARLA grows fast and steady, widening the range of solutions provided and opening the way for the different approaches to autonomous driving. It does so while never forgetting its open-source nature. The project is transparent, acting as a white box where anybody is granted access to the tools and the development community. In that democratization is where CARLA finds its value.
Talking about how CARLA grows means talking about a community of developers who dive together into the thorough question of autonomous driving. Everybody is free to explore with CARLA, find their own solutions and then share their achievements with the rest of the community.

This documentation will be a companion along the way. The next page contains quick start instructions for those eager to install a CARLA release. There is also a build guide for Linux and Windows. This will make CARLA from repository and allow to dive full-length into its features.

Welcome to CARLA.

<div class="build-buttons"> <p> <a href="../build_linux" target="_blank" class="btn btn-neutral" title="Go to the latest CARLA release"> <b>Linux</b> build</a> </p> <p> <a href="../build_windows" target="_blank" class="btn btn-neutral" title="Go to the latest CARLA release"> <b>Windows</b> build</a> </p> </div>