### Install CARLA Python Example Prerequisites Source: https://carla.readthedocs.io/en/latest/start_quickstart Install the necessary prerequisite packages for CARLA Python client example scripts. Ensure you are in the 'PythonAPI/examples' directory. ```bash cd PythonAPI/examples python3 -m pip install -r requirements.txt ``` -------------------------------- ### Install PyTorch for DQN Example Source: https://carla.readthedocs.io/en/latest/tuto_G_rllib_integration Installs the necessary PyTorch dependencies for the DQN example. Ensure you have the requirements file available. ```bash python3 -m pip install -r dqn_example/dqn_requirements.txt ``` -------------------------------- ### Install Example Script Requirements Source: https://carla.readthedocs.io/en/latest/build_linux Installs the Python dependencies required to run the CARLA example scripts. This should be done in the directory containing the example scripts. ```bash # Terminal A cd ${CARLA_UE4_ROOT}/PythonAPI/examples python3 -m pip install -r requirements.txt ``` -------------------------------- ### Start CARLA Source: https://carla.readthedocs.io/en/latest/nvidia_cosmos_transfer Navigate to the root folder of your CARLA installation and execute the launch script to start CARLA. ```bash ./CarlaUE4.sh ``` -------------------------------- ### Run NuRec Installation Script Source: https://carla.readthedocs.io/en/latest/nvidia_nurec Navigates to the NuRec example directory within the CARLA PythonAPI, activates the virtual environment, and runs the installation script. This script installs prerequisites, Python packages, sets environment variables, and downloads the dataset. ```bash source vecarla/bin/activate # Activate the venv cd ${CARLA_ROOT}/PythonAPI/examples/nvidia/nurec/ ./install_nurec.sh ``` -------------------------------- ### Install CARLA Python Client Source: https://carla.readthedocs.io/en/latest/nvidia_cosmos_transfer Install the CARLA Python client wheel file. Ensure you replace the example filename with your actual file. ```bash # Replace carla-0.9.16-cp310-cp310-linux_x86_64.whl with your actual filename pip install carla-0.9.16-cp310-cp310-linux_x86_64.whl ``` -------------------------------- ### Run Example Script Source: https://carla.readthedocs.io/en/latest/build_faq Navigate to the example scripts directory and run a specific example. Use this to test if the build was successful. ```bash cd PythonAPI/examples python3 dynamic_weather.py ``` -------------------------------- ### Batch Spawning and Autopilot Setup Source: https://carla.readthedocs.io/en/latest/adv_traffic_manager An example script demonstrating how to create a TM instance, pass a port as an argument, and register spawned vehicles to it by setting autopilot in a batch. It also shows how to set a global speed difference. ```python traffic_manager = client.get_trafficmanager(args.tm-port) tm_port = traffic_manager.get_port() ... batch.append(SpawnActor(blueprint, transform).then(SetAutopilot(FutureActor, True,tm_port))) ... traffic_manager.global_percentage_speed_difference(30.0) ``` -------------------------------- ### Install CARLA Python API Wheel (Python 3.8 Example) Source: https://carla.readthedocs.io/en/latest/build_linux Installs the compiled CARLA Python API wheel package for a specific CARLA version and Python version. This command should be run after the wheel is generated. ```bash # CARLA 0.9.16, Python 3.8 python3 -m pip install ${CARLA_UE4_ROOT}/PythonAPI/carla/dist/carla-0.9.16-cp38-linux_x86_64.whl ``` -------------------------------- ### Install CARLA Python API Wheel (Python 3.10 Example) Source: https://carla.readthedocs.io/en/latest/build_linux Installs the compiled CARLA Python API wheel package for a specific CARLA version and Python version. This command should be run after the wheel is generated. ```bash # CARLA 0.9.16, Python 3.10 #python3 -m pip install ${CARLA_UE4_ROOT}/PythonAPI/carla/dist/carla-0.9.16-cp310-linux_x86_64.whl ``` -------------------------------- ### Install MkDocs Source: https://carla.readthedocs.io/en/latest/cont_contribution_guidelines Install MkDocs, a static site generator used for building documentation, using pip. ```bash sudo pip install mkdocs ``` -------------------------------- ### Install Requirements and Generate Traffic Source: https://carla.readthedocs.io/en/latest/build_windows In a new terminal, navigate to the examples directory and run these commands to install requirements and generate traffic in the CARLA simulation. ```bash cd PythonAPI\examples python3 -m pip install -r requirements.txt python3 generate_traffic.py ``` -------------------------------- ### Run CARLA Examples Source: https://carla.readthedocs.io/en/latest/build_linux Executes the example scripts for CARLA. This command requires specifying the host and port for the simulator connection. ```bash make run-examples ARGS="localhost " ``` -------------------------------- ### Install and Configure SUMO for Co-simulation Source: https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data Commands to install SUMO dependencies and set the required environment variable. ```bash sudo add-apt-repository ppa:sumo/stable sudo apt-get update sudo apt-get install sumo sumo-tools sumo-doc ``` ```bash echo "export SUMO_HOME=/usr/share/sumo" >> ~/.bashrc && source ~/.bashrc ``` -------------------------------- ### Create DQN Training AMI on AWS Source: https://carla.readthedocs.io/en/latest/tuto_G_rllib_integration Creates a training AMI specifically for the DQN example on AWS. This command requires the DQN autoscaler configuration file and installation script. ```bash python3 aws_helper.py create-image --name --installation-scripts install/install.sh --instance-type --volume-size ``` -------------------------------- ### Setup and Build Unreal Engine Source: https://carla.readthedocs.io/en/latest/build_linux Executes the setup and project file generation scripts, followed by the compilation of Unreal Engine. This process can take a significant amount of time. Do not use the -j flag with make, as Clang manages core usage automatically. ```bash ./Setup.sh && ./GenerateProjectFiles.sh && make ``` -------------------------------- ### Install Python Dependencies Source: https://carla.readthedocs.io/en/latest/build_windows Install necessary Python dependencies, setuptools and wheel, using pip. These are required for building CARLA. ```bash python3 -m pip install --user setuptools python3 -m pip install --user wheel ``` -------------------------------- ### Install Docker on Ubuntu Source: https://carla.readthedocs.io/en/latest/nvidia_nurec Installs Docker and its components on Ubuntu by adding the Docker repository and using apt-get. Ensure Docker is installed before running the NuRec install script. ```bash sudo install -m 0755 -d /etc/apt/keyrings curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg \ --dearmor -o /etc/apt/keyrings/docker.gpg sudo chmod a+r /etc/apt/keyrings/docker.gpg sudo apt-get update sudo apt-get install -y docker-ce docker-ce-cli \ containerd.io docker-buildx-plugin docker-compose-plugin ``` -------------------------------- ### Start Primary Server (No Rendering) Source: https://carla.readthedocs.io/en/latest/adv_multigpu Use this command to start the primary CARLA server without any rendering capabilities, freeing up a GPU. The server will listen for secondary servers on the default port 2002. ```bash ./CarlaUE4.sh -nullrhi ``` -------------------------------- ### Run Dynamic Weather Example Source: https://carla.readthedocs.io/en/latest/build_windows In a separate terminal, navigate to the examples directory and run this command to activate dynamic weather in the CARLA simulation. ```bash cd PythonAPI\examples python3 dynamic_weather.py ``` -------------------------------- ### Run SUMO-CARLA Synchronization Source: https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data Launch the synchronization script and trigger the simulation start. ```bash cd ~/carla/Co-Simulation/Sumo python3 run_synchronization.py examples/Town01.sumocfg --sumo-gui ``` ```text > "Play" on SUMO window. ``` -------------------------------- ### Install Python API Prerequisites Source: https://carla.readthedocs.io/en/latest/build_linux Installs the necessary Python packages for the CARLA Python API client. Ensure the CARLA_UE4_ROOT environment variable is set. ```bash python3 -m pip install --upgrade -r ${CARLA_UE4_ROOT}/PythonAPI/carla/requirements.txt ``` -------------------------------- ### Install Benchmark Dependencies Source: https://carla.readthedocs.io/en/latest/adv_benchmarking Installs the necessary Python packages for the CARLA benchmarking script. Ensure these are installed before running the benchmark. ```bash python -m pip install -U py-cpuinfo==5.0.0 python -m pip install psutil python -m pip install python-tr python -m pip install gpuinfo python -m pip install GPUtil ``` -------------------------------- ### Load World and Start Recorder Source: https://carla.readthedocs.io/en/latest/foundations Use the client object to load a new world and start recording the simulation. Recordings are saved to a .log file. ```python client.load_world('Town07') client.start_recorder('recording.log') ``` -------------------------------- ### Install Colcon for Building Source: https://carla.readthedocs.io/en/latest/adv_rss Installs the colcon build tool, which is required for building CARLA with RSS integration. Install it for your user. ```bash python3 -m pip install --user -U colcon-common-extensions ``` -------------------------------- ### Install CARLA Python Client from PyPI Source: https://carla.readthedocs.io/en/latest/start_quickstart Install the official CARLA Python client library from PyPI using pip. You can specify a particular version if needed. ```bash python3 -m pip install carla # carla==0.9.14 <= For a specific version ``` -------------------------------- ### Install X Server Dependencies for Vulkan Source: https://carla.readthedocs.io/en/latest/adv_rendering_options Install essential packages for X server and Vulkan support on Ubuntu, required for CARLA's Vulkan off-screen rendering. ```bash sudo apt-get install -y xserver-xorg mesa-utils libvulkan1 ``` -------------------------------- ### Sync DQN Example Files to AWS Source: https://carla.readthedocs.io/en/latest/tuto_G_rllib_integration Synchronizes local DQN example files and RLlib integration code with the remote AWS cluster. This is useful after making local modifications. ```bash ray rsync-up dqn_example/dqn_autoscaler.yaml dqn_example . ray rsync-up dqn_example/dqn_autoscaler.yaml rllib_integration . ``` -------------------------------- ### Install Specific Setuptools Version Source: https://carla.readthedocs.io/en/latest/build_faq An AttributeError: module 'carla' has no attribute 'Client' can occur if setuptools is not at the correct version. Install version 47.3.1 to resolve this. ```bash python3 -m pip install -Iv setuptools==47.3.1 ``` -------------------------------- ### Test Docker Installation Source: https://carla.readthedocs.io/en/latest/nvidia_nurec Tests if Docker is installed and functioning correctly by running the 'hello-world' container. If an error occurs, the user may need to be added to the Docker group. ```bash docker run hello-world ``` -------------------------------- ### Activate Virtual Environment and Install Requirements Source: https://carla.readthedocs.io/en/latest/build_linux Activates the newly created virtual environment and installs the Python API requirements within that isolated environment. ```bash source myenv/bin/activate (myenv): python3 -m pip install --upgrade -r ${CARLA_UE4_ROOT}/PythonAPI/carla/requirements.txt ``` -------------------------------- ### Activate venv and Install Requirements Source: https://carla.readthedocs.io/en/latest/nvidia_nurec Activate your virtual environment and install necessary Python packages using the provided requirements file. Ensure CARLA is sourced correctly. ```bash source vecarla/bin/activate # Activate the venv python3 -m pip install -r ${CARLA_ROOT}/PythonAPI/carla/requirements.txt ``` -------------------------------- ### Start CARLA Source: https://carla.readthedocs.io/en/latest/adv_benchmarking Commands to launch the CARLA simulator on Linux, Windows, or from source. ```bash # Linux: ./CarlaUE4.sh # Windows: CarlaUE4.exe # Source: make launch ``` -------------------------------- ### Running Traffic Manager Example with Deterministic Seed Source: https://carla.readthedocs.io/en/latest/adv_traffic_manager This command demonstrates how to run the `generate_traffic.py` example script with a specified number of autopilot actors and a seed value for deterministic mode. ```bash cd PythonAPI/examples python3 generate_traffic.py -n 50 --seed 9 ``` -------------------------------- ### CarSim .sim file example (Ubuntu) Source: https://carla.readthedocs.io/en/latest/tuto_G_carsim_integration This is an example of a .sim file adapted for Ubuntu. It uses Linux-style paths and specifies the shared object (.so) file for the CarSim solver. ```plaintext SIMFILE FILEBASE /path/to/LastRun INPUT /path/to/Run_all.par INPUTARCHIVE /path/to/LastRun_all.par ECHO /path/to/LastRun_echo.par FINAL /path/to/LastRun_end.par LOGFILE /path/to/LastRun_log.txt ERDFILE /path/to/LastRun.vs PROGDIR /opt/carsim_2020.0/lib64/ DATADIR . PRODUCT_ID CarSim PRODUCT_VER 2020.0 VEHICLE_CODE i_i SOFILE /opt/carsim_2020.0/lib64/libcarsim.so.2020.0 END ``` -------------------------------- ### Start Primary Server (Custom Port) Source: https://carla.readthedocs.io/en/latest/adv_multigpu Start the primary CARLA server without rendering capabilities and specify a custom TCP port for secondary servers to connect to. This is useful if the default port 2002 is in use. ```bash ./CarlaUE4.sh -nullrhi -carla-primary-port=3002 ``` -------------------------------- ### Initialize Ego Vehicle Tutorial Script Source: https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data Sets up the CARLA client and argument parsing for the tutorial script. ```python import carla import argparse import time import logging import random def main(): argparser = argparse.ArgumentParser( description=__doc__) argparser.add_argument( '--host', metavar='H', default='127.0.0.1', help='IP of the host server (default: 127.0.0.1)') argparser.add_argument( '-p', '--port', metavar='P', default=2000, type=int, help='TCP port to listen to (default: 2000)') args = argparser.parse_args() logging.basicConfig(format='%(levelname)s: %(message)s', level=logging.INFO) client = carla.Client(args.host, args.port) client.set_timeout(10.0) try: world = client.get_world() ego_vehicle = None ego_cam = None ego_col = None ego_lane = None ego_obs = None ego_gnss = None ego_imu = None ``` -------------------------------- ### Serve Documentation Locally Source: https://carla.readthedocs.io/en/latest/cont_contribution_guidelines Run a local server to visualize the documentation as it is being written. Access the documentation at http://127.0.0.1:8000. ```bash mkdocs serve ``` -------------------------------- ### Clone RLlib Integration Repository Source: https://carla.readthedocs.io/en/latest/tuto_G_rllib_integration Clone the RLlib integration repository from GitHub to get started. ```bash git clone https://github.com/carla-simulator/rllib-integration.git ``` -------------------------------- ### CARLA Simulator Setup and Sensor Initialization Source: https://carla.readthedocs.io/en/latest/tuto_G_bounding_boxes This snippet sets up the CARLA simulator, spawns a vehicle and an RGB camera attached to it, and configures synchronous mode for sensor data. It also prepares a queue to listen for camera images. ```Python import carla import math import random import time import queue import numpy as np import cv2 client = carla.Client('localhost', 2000) world = client.get_world() bp_lib = world.get_blueprint_library() # Get the map spawn points spawn_points = world.get_map().get_spawn_points() # spawn vehicle vehicle_bp =bp_lib.find('vehicle.lincoln.mkz_2020') vehicle = world.try_spawn_actor(vehicle_bp, random.choice(spawn_points)) # spawn camera camera_bp = bp_lib.find('sensor.camera.rgb') camera_init_trans = carla.Transform(carla.Location(z=2)) camera = world.spawn_actor(camera_bp, camera_init_trans, attach_to=vehicle) vehicle.set_autopilot(True) # Set up the simulator in synchronous mode settings = world.get_settings() settings.synchronous_mode = True # Enables synchronous mode settings.fixed_delta_seconds = 0.05 world.apply_settings(settings) # Create a queue to store and retrieve the sensor data image_queue = queue.Queue() camera.listen(image_queue.put) ``` -------------------------------- ### Get Waypoints from Junction Source: https://carla.readthedocs.io/en/latest/core_map Retrieve pairs of waypoints marking the start and end boundaries of lanes within a junction. ```python waypoints_junc = my_junction.get_waypoints() ``` -------------------------------- ### Update CARLA Packaged Release Source: https://carla.readthedocs.io/en/latest/build_update Commands to update a CARLA packaged release by deleting the current version and following the quick start installation. ```bash # Update a CARLA packaged release. # 1. Delete the current one. # 2. Follow the Quick start installation to get the one desired. # Update Linux build. git checkout master make clean git pull origin master ./Update.sh # Update Windows build. git checkout master make clean git pull origin master # Erase the content in `Unreal/CarlaUE4/Content/Carla`. # Go to `\Util\ContentVersions.txt`. # Download the latest content. # Extract the new content in `Unreal\CarlaUE4\Content\Carla` # Get development assets. # Delete the `/Carla` folder containing previous assets. # Go to the main carla folder. git clone https://bitbucket.org/carla-simulator/carla-content Unreal/CarlaUE4/Content/Carla ``` -------------------------------- ### Initialize AI Controller for Pedestrian Source: https://carla.readthedocs.io/en/latest/tuto_G_pedestrian_bones Initializes and starts an AI controller for a pedestrian to navigate the map autonomously. This code is typically run once during setup. ```python controller_bp = world.get_blueprint_library().find('controller.ai.walker') controller = world.spawn_actor(controller_bp, pedestrian.get_transform(), pedestrian) controller.start() controller.go_to_location(world.get_random_location_from_navigation()) ``` -------------------------------- ### Run X Server for Vulkan Source: https://carla.readthedocs.io/en/latest/adv_rendering_options Start the X server on display :0 in the background, a prerequisite for running CARLA with Vulkan off-screen. ```bash sudo X :0 & ``` -------------------------------- ### Setup CARLA Cosmos Client Conda Environment Source: https://carla.readthedocs.io/en/latest/nvidia_cosmos_transfer Create and activate a conda environment for the CARLA Cosmos client and install project dependencies. ```bash cd PythonAPI/examples/nvidia/cosmos # Create the carla-cosmos-client conda environment. conda env create --file client/carla-cosmos-client.yaml # Activate the carla-cosmos-client conda environment. conda activate carla-cosmos-client # Install the dependencies. pip install -r requirements.txt pip install -r client/requirements_client.txt ``` -------------------------------- ### List Available Maps in CARLA Source: https://carla.readthedocs.io/en/latest/tuto_first_steps Use this command to get a list of all maps currently available in your CARLA installation. This includes default maps and any custom or imported maps. ```python client.get_available_maps() ``` -------------------------------- ### Example Folder Structure for Props Source: https://carla.readthedocs.io/en/latest/tuto_A_add_props Illustrates the required folder structure within the CARLA 'Import' directory for organizing prop assets and their associated files. ```text Import │ ├── Package01 │ ├── Package01.json │ └── Props │ ├── Prop01 │ │ ├── Prop01_Diff.png │ │ ├── Prop01_Norm.png │ │ ├── Prop01_Spec.png │ │ └── Prop01.fbx │ └── Prop02 │ └── Prop02.fbx └── Package02 ├── Packag02.json └── Props └── Prop03 └── Prop03.fbx ``` -------------------------------- ### Launch CARLA Server on Ubuntu Source: https://carla.readthedocs.io/en/latest/start_quickstart Navigate to the CARLA root directory and execute the launch script. Ensure the server is running before connecting a client. ```bash cd path/to/carla/root ./CarlaUE4.sh ``` -------------------------------- ### Install Python Bindings Dependencies Source: https://carla.readthedocs.io/en/latest/adv_rss Installs additional Python dependencies required for the CARLA Python API bindings related to RSS. Ensure you have Python 3 installed. ```bash sudo apt-get install castxml python3 -m pip install --user pygccxml pyplusplus ``` -------------------------------- ### Initialize CARLA Client Source: https://carla.readthedocs.io/en/latest/tuto_G_control_walker_skeletons Establishes a connection to the CARLA simulator. Ensure the simulator is running and accessible at the specified address and port. ```python client = carla.Client('127.0.0.1', 2000) client.set_timeout(2.0) ``` -------------------------------- ### Install Meshlab Source: https://carla.readthedocs.io/en/latest/tuto_G_retrieve_data Installs Meshlab on a Debian-based system for visualizing LIDAR PLY files. ```bash sudo apt-get update -y sudo apt-get install -y meshlab ``` -------------------------------- ### Run CARLA-SUMO Co-simulation Source: https://carla.readthedocs.io/en/latest/adv_sumo This command initiates the co-simulation between CARLA and SUMO. It requires the path to the SUMO configuration file and can be customized with options like traffic light management and enabling the SUMO GUI. ```bash python3 run_synchronization.py --tls-manager carla --sumo-gui ``` -------------------------------- ### Launch CARLA Server on Windows Source: https://carla.readthedocs.io/en/latest/start_quickstart Navigate to the CARLA root directory and execute the server executable. Ensure the server is running before connecting a client. ```bash cd path/to/carla/root CarlaUE4.exe ``` -------------------------------- ### Launch CARLA Server Source: https://carla.readthedocs.io/en/latest/build_update Starts the CARLA server in spectator view to verify the update. ```bash make launch ``` -------------------------------- ### Install NVIDIA Driver Silently Source: https://carla.readthedocs.io/en/latest/adv_rendering_options Install the downloaded NVIDIA driver using the provided script with non-interactive options. ```bash sudo /bin/bash NVIDIA-Linux-x86_64-450.57.run --accept-license --no-questions --ui=none ``` -------------------------------- ### Install Local Python Requirements Source: https://carla.readthedocs.io/en/latest/tuto_G_rllib_integration Navigate to the RLlib integration repository and install the required Python packages using pip. ```bash python3 -m pip install -r requirements.txt ``` -------------------------------- ### Install CARLA Python Module Source: https://carla.readthedocs.io/en/latest/foundations Install the CARLA Python API module using pip. This command should be run in your terminal. ```bash python3 -m pip install carla ``` -------------------------------- ### Run SUMO Co-simulation Example Source: https://carla.readthedocs.io/en/latest/adv_sumo Executes the SUMO co-simulation synchronization script using a specific Town04 configuration file. The --sumo-gui flag enables the SUMO graphical interface. ```python cd ~/carla/Co-Simulation/Sumo python3 run_synchronization.py examples/Town04.sumocfg --sumo-gui ``` -------------------------------- ### Install Doxygen and Graphviz on Linux Source: https://carla.readthedocs.io/en/latest/ref_cpp Installs Doxygen and Graphviz on Linux systems, which are required for generating C++ documentation and graph drawings. ```bash # linux > sudo apt-get install doxygen graphviz ``` -------------------------------- ### Launch Unreal Engine Editor Source: https://carla.readthedocs.io/en/latest/build_linux Navigates to the Linux binaries directory of the Unreal Engine installation and launches the editor to verify the installation. ```bash cd ~/UnrealEngine_4.26/Engine/Binaries/Linux && ./UE4Editor ``` -------------------------------- ### Check Pip Version Source: https://carla.readthedocs.io/en/latest/build_windows Verify the installed version of pip for Python 3. This is required for installing CARLA Python API dependencies. ```bash python3 -m pip -V ``` -------------------------------- ### Create Training AMI on AWS Source: https://carla.readthedocs.io/en/latest/tuto_G_rllib_integration Uses the aws_helper.py script to create a training AMI on AWS. Specify the AMI name, installation scripts, instance type, and volume size. ```bash python3 aws_helper.py create-image --name --installation-scripts --instance-type --volume-size ``` -------------------------------- ### Uninstall CARLA APT Package Source: https://carla.readthedocs.io/en/latest/build_faq Command to remove a CARLA installation that was installed via apt-get. This can help resolve conflicts with custom builds. ```bash sudo apt-get purge carla-simulator ``` -------------------------------- ### Run CARLA Python Example Scripts Source: https://carla.readthedocs.io/en/latest/start_quickstart Execute traffic generation and manual control scripts from the PythonAPI/examples directory. These scripts require the CARLA server to be running. ```bash # Run generate Terminal A cd PythonAPI\examples python3 generate_traffic.py # Terminal B cd PythonAPI\examples python3 manual_control.py ``` -------------------------------- ### Start Secondary Server (GPU 0) Source: https://carla.readthedocs.io/en/latest/adv_multigpu Launch a secondary CARLA server to handle rendering on a specific GPU (device 0). It connects to the primary server on localhost using the default port 2002. The RPC port is set to 3000 to avoid conflicts. ```bash ./CarlaUE4.sh -carla-rpc-port=3000 -carla-primary-host=127.0.0.1 -ini:[/Script/Engine.RendererSettings]:r.GraphicsAdapter=0 ``` -------------------------------- ### Install Ubuntu Dependencies for RSS Source: https://carla.readthedocs.io/en/latest/adv_rss Installs necessary Ubuntu dependencies for building RSS and its components. Ensure your Ubuntu version is 16.04 or higher. ```bash sudo apt-get install libgtest-dev libpython-dev libpugixml-dev libtbb-dev ``` -------------------------------- ### CARLA Map Georeference Example Source: https://carla.readthedocs.io/en/latest/coordinates An example of the georeference tag within an OpenDRIVE file header, defining map projection and center location. ```xml
... ``` -------------------------------- ### Launch CARLA Server Source: https://carla.readthedocs.io/en/latest/nvidia_nurec Navigate to the CARLA root directory and execute the CARLA server. Ensure CARLA_ROOT is set correctly. ```bash cd ${CARLA_ROOT} ./CarlaUE4.sh ```