autoware_carla_interface

ROS 2 / Autoware Universe bridge for CARLA simulator

Thanks to https://github.com/gezp for ROS 2 Humble support for CARLA Communication. This ros package enables communication between Autoware and CARLA for autonomous driving simulation.

Supported Environment

ubuntu	ros	carla	autoware
22.04	humble	0.9.15	Main

Setup

Install

Prerequisites

1. Install CARLA 0.9.15: Follow the CARLA Installation Guide

2. Install CARLA Python Package: Install CARLA 0.9.15 ROS 2 Humble communication package

   • Option A: Install the wheel using pip
   • Option B: Add the egg file to your PYTHONPATH

3. Download CARLA Lanelet2 Maps: Get the y-axis inverted maps from CARLA Autoware Contents

Map Setup

1. Download the maps (y-axis inverted version) to an arbitrary location
2. Create the map folder structure in $HOME/autoware_map:
   • Rename point_cloud/Town01.pcd → $HOME/autoware_map/Town01/pointcloud_map.pcd
   • Rename vector_maps/lanelet2/Town01.osm → $HOME/autoware_map/Town01/lanelet2_map.osm

3. Create $HOME/autoware_map/Town01/map_projector_info.yaml with:

   projector_type: Local
   

Build

colcon build --symlink-install --cmake-args -DCMAKE_BUILD_TYPE=Release

Run

1. Run carla, change map, spawn object if you need

   cd CARLA
   ./CarlaUE4.sh -prefernvidia -quality-level=Low -RenderOffScreen
   

2. Run Autoware with CARLA

   ros2 launch autoware_launch e2e_simulator.launch.xml \
       map_path:=$HOME/autoware_map/Town01 \
       vehicle_model:=sample_vehicle \
       sensor_model:=carla_sensor_kit \
       simulator_type:=carla \
       carla_map:=Town01
   

3. Set initial pose (Init by GNSS)

4. Set goal position
5. Wait for planning
6. Engage

Viewing Multi-Camera View in RViz

The carla_sensor_kit includes 6 cameras providing 360-degree coverage (Front, Front-Left, Front-Right, Back, Back-Left, Back-Right). A multi-camera combiner node automatically combines all camera feeds into a single 2x3 grid view.

To view the combined camera feed in RViz:

1. In the Displays panel (left side), click the "Add" button
2. Select the "By topic" tab
3. Navigate to /sensing/camera/all_cameras/image_raw
4. Select "Image" display type
5. Click OK

The combined view shows all 6 cameras with labels: FL (Front-Left), F (Front), FR (Front-Right), BL (Back-Left), B (Back), BR (Back-Right).

Note: If you don't need the multi-camera combiner (to save CPU resources), you can comment out the following line in launch/autoware_carla_interface.launch.xml:

<!-- Multi-camera combiner for RViz visualization -->
<!-- <node pkg="autoware_carla_interface" exec="multi_camera_combiner" output="screen"/> -->

Inner-workings / Algorithms

The InitializeInterface class is key to setting up both the CARLA world and the ego vehicle. It fetches configuration parameters through the autoware_carla_interface.launch.xml.

The main simulation loop runs within the carla_ros2_interface class. This loop ticks simulation time inside the CARLA simulator at fixed_delta_seconds time, where data is received and published as ROS 2 messages at frequencies defined in self.sensor_frequencies.

Ego vehicle commands from Autoware are processed through the autoware_raw_vehicle_cmd_converter, which calibrates these commands for CARLA. The calibrated commands are then fed directly into CARLA control via CarlaDataProvider.

Configurable Parameters for World Loading

All the key parameters can be configured in autoware_carla_interface.launch.xml.

Name	Type	Default Value	Description
host	string	"localhost"	Hostname for the CARLA server
port	int	"2000"	Port number for the CARLA server
timeout	int	20	Timeout for the CARLA client
ego_vehicle_role_name	string	"ego_vehicle"	Role name for the ego vehicle
vehicle_type	string	"vehicle.toyota.prius"	Blueprint ID of the vehicle to spawn. The Blueprint ID of vehicles can be found in CARLA Blueprint ID
spawn_point	string	None	Coordinates for spawning the ego vehicle (None is random). Format = [x, y, z, roll, pitch, yaw]
carla_map	string	"Town01"	Name of the map to load in CARLA
sync_mode	bool	True	Boolean flag to set synchronous mode in CARLA
fixed_delta_seconds	double	0.05	Time step for the simulation (related to client FPS)
use_traffic_manager	bool	False	Boolean flag to set traffic manager in CARLA
max_real_delta_seconds	double	0.05	Parameter to limit the simulation speed below fixed_delta_seconds
sensor_kit_name	string	"carla_sensor_kit_description"	Name of the sensor kit package to use for sensor configuration. Should be the *_description package containing config/sensor_kit_calibration.yaml
sensor_mapping_file	string	"$(find-pkg-share autoware_carla_interface)/config/sensor_mapping.yaml"	Path to sensor mapping YAML configuration file
config_file	string	"$(find-pkg-share autoware_carla_interface)/raw_vehicle_cmd_converter.param.yaml"	Control mapping file to be used in autoware_raw_vehicle_cmd_converter. Current control are calibrated based on vehicle.toyota.prius Blueprints ID in CARLA. Changing the vehicle type may need a recalibration.

Sensor Configuration

The interface uses the carla_sensor_kit which provides 6 cameras for 360-degree coverage, LiDAR, IMU, and GNSS sensors. Sensor configurations are dynamically loaded from Autoware sensor kit calibration files through two configuration files:

1. Sensor Kit Calibration (from Autoware sensor kit)

Located in <sensor_kit_name>_description/config/sensor_kit_calibration.yaml

Defines sensor positions and orientations relative to base_link (rear axle center). Example:

sensor_kit_base_link:
  CAM_FRONT/camera_link:
    x: 2.225
    y: 0.000
    z: 1.600
    roll: 0.000
    pitch: 0.000
    yaw: 0.000 # Angles in radians

2. Sensor Mapping (CARLA-specific)

Located in config/sensor_mapping.yaml

Maps Autoware sensors to CARLA sensor types and parameters. Key sections:

• default_sensor_kit_name: Default sensor kit to use (e.g., carla_sensor_kit_description)
• sensor_mappings: Maps each sensor to CARLA type and ROS topics
• enabled_sensors: List of sensors to spawn in CARLA
• vehicle_config (optional): Vehicle parameters like wheelbase

Example sensor mapping:

sensor_mappings:
  CAM_FRONT/camera_link:
    carla_type: sensor.camera.rgb
    id: "CAM_FRONT"
    ros_config:
      frame_id: "CAM_FRONT/camera_optical_link"
      topic_image: "/sensing/camera/CAM_FRONT/image_raw"
      frequency_hz: 11
    parameters:
      image_size_x: 1600
      image_size_y: 900
      fov: 70.0

For CARLA sensor parameters, see CARLA Sensor Reference.

World Loading

The carla_ros.py sets up the CARLA world:

1. Client Connection:

   client = carla.Client(self.local_host, self.port)
   client.set_timeout(self.timeout)
   

2. Load the Map:

   Map loaded in CARLA world with map according to carla_map parameter.

   client.load_world(self.map_name)
   self.world = client.get_world()
   

3. Spawn Ego Vehicle:

   Vehicle are spawn according to vehicle_type, spawn_point, and agent_role_name parameter.

   spawn_point = carla.Transform()
   point_items = self.spawn_point.split(",")
   if len(point_items) == 6:
      spawn_point.location.x = float(point_items[0])
      spawn_point.location.y = float(point_items[1])
      spawn_point.location.z = float(point_items[2]) + 2
      spawn_point.rotation.roll = float(point_items[3])
      spawn_point.rotation.pitch = float(point_items[4])
      spawn_point.rotation.yaw = float(point_items[5])
   CarlaDataProvider.request_new_actor(self.vehicle_type, spawn_point, self.agent_role_name)
   

Traffic Light Recognition

The maps provided by the Carla Simulator (Carla Lanelet2 Maps) currently lack proper traffic light components for Autoware and have different latitude and longitude coordinates compared to the pointcloud map. To enable traffic light recognition, follow the steps below to modify the maps.

• Options to Modify the Map

  • A. Create a New Map from Scratch
  • Use the TIER IV Vector Map Builder to create a new map.
  • B. Modify the Existing Carla Lanelet2 Maps
  • Adjust the longitude and latitude of the Carla Lanelet2 Maps to align with the PCD (origin).
    • Use this tool to modify the coordinates.
    • Snap Lanelet with PCD and add the traffic lights using the TIER IV Vector Map Builder.

• When using the TIER IV Vector Map Builder, you must convert the PCD format from binary_compressed to ascii. You can use pcl_tools for this conversion.
• For reference, an example of Town01 with added traffic lights at one intersection can be downloaded here.

Tips

• Misalignment might occurs during initialization, pressing init by gnss button should fix it.
• Changing the fixed_delta_seconds can increase the simulation tick (default 0.05 s), some sensor params in sensor_mapping.yaml need to be adjusted when it is changed (example: LIDAR rotation frequency should match the FPS).

Known Issues and Future Works

• Testing on procedural maps (Adv Digital Twin): Currently unable to test due to failures in creating the Adv Digital Twin map.
• Traffic light recognition: The default CARLA Lanelet2 maps lack proper traffic light regulatory elements. See the "Traffic Light Recognition" section above for workarounds.
• LiDAR concatenation: When using multiple LiDARs, you may need to uncomment the lidar concatenation relay in the launch file (currently disabled by default).