Import FBX 3D models into CARLA as props that can be placed through its Python API. Handles category tags, measured dimensions, asset registration, and spawn checks for individual files or folders of models.
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Add a message type to CARLA's native ROS 2 interface. Create its C++ data structure, serialization code for transmission, type identity hash, registration, and tests, with Docker-based hash calculation and build checks.
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Downloads CARLA release packages, nightly builds, source code, or Docker images, then reports their locations and environment variables for follow-up setup. Supports extra maps and resumable downloads, helping prepare the files needed for subsequent installation or building.
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Control traffic lights in a running CARLA simulation. Change their color, switch them off, hold a fixed state, adjust phase durations, or restore normal cycling, targeting individual lights, junctions, nearby lights, or the whole map.
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Check whether a CARLA feature is usable in the current environment and has a verified procedure. Review known failures, inspect build settings, and identify differences between client, server, and source versions before planning work.
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Import an FBX character into a CARLA source build as a pedestrian available through the Python API. Check its GEN3 skeleton, create assets and a walker blueprint, register it, and verify spawning, ground placement, and movement.
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Control street, building, and vehicle light sources in CARLA. Switch groups on or off, adjust their color and brightness, and enable automatic nighttime lighting to prepare illuminated city scenes or blackouts.
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Adjust how autopilot vehicles behave in CARLA, including speed, following distance, traffic light responses, and lane changes. Apply settings across traffic or to individual vehicles, and configure seeds and synchronization for repeatable traffic runs.
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Inspect a running CARLA simulation and identify vehicles or pedestrians by type, role, color, or proximity. Retrieve their IDs, scene snapshots, static object bounds, ground positions, and expected ROS 2 topics with reasons for missing publications.
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Extend CARLA’s native ROS 2 interface to publish sensor data or receive vehicle commands. Covers topic implementation, registration, data connections, and verification, plus adding middleware, the communication layer used to exchange messages.
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Replay a recorded CARLA simulation in full or over a selected time range. Change playback speed, follow a particular vehicle, restore recorded weather, or regenerate sensor data to examine the run again.
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Create and edit CARLA driving routes by placing waypoints and scenario triggers in the simulator. Inspect routes visually, review summary tables, check XML structure and trigger positions, and convert older route files to the 2.x format.
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Record a running CARLA simulation to a .log file for later replay or inspection. Capture object creation, movement, and traffic-light states, optionally include controls and velocities, and verify that the recording contains simulation frames.
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Package a CARLA Leaderboard agent into a Docker image for submission. It checks required directories and Python package files, supports ROS variants, and verifies that dependencies import and the agent loads inside the image.
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Inspect data published by a ROS 2-enabled CARLA server using Docker, without installing ROS 2 locally. Check topic contents and rates, run a sensor-equipped vehicle demo, and view lidar data and supported map markers in RViz2.
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Run CARLA routes with a driving agent through ScenarioRunner, including scenarios available only in route mode. Inspect route contents, execute one or all routes, and obtain reports on completion, collisions, traffic lights, and other criteria.
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Populate a running CARLA simulation with autonomous traffic, evenly spaced vehicles in one lane, or a single vehicle for control and sensors. Filter vehicle models, keep automated driving active, and remove vehicles when the scene is finished.
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Explore roads, lanes, and junctions in a CARLA simulation map through text reports and visual overlays. Locate places described in everyday language, inspect nearby lane details, and trace a path forward or backward along a lane.
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Read and change a running CARLA server’s timing, physics substeps, and rendering settings. Switch between client-controlled steps and automatic progression, keep Traffic Manager synchronization aligned, and read back the settings to verify each change.
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Manually drive a vehicle in CARLA, set a target speed, operate lights and doors, and adjust mass or drag. You can also inspect the command topics used to control the main vehicle through ROS 2.
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Evaluate a driving agent on CARLA Leaderboard routes after checking the required setup. Select routes and repetitions, save driving scores and infractions, record runs, and resume interrupted evaluations from a saved checkpoint.
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Build distributable CARLA releases or asset packages containing selected maps and props. It prepares content for runtime use, checks output files, supports destination changes, and preserves native ROS 2 support when explicitly enabled.
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Add pedestrians to a CARLA map and let them walk autonomously. Adjust crowd size, walking speed, road-crossing frequency, and placement seeds, create stationary crowds, and remove pedestrians together with their movement controllers in the correct order.
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Turn a written traffic situation into a Scenic file, which describes possible scenes using placement rules and constraints. Select suitable maps and actors, then check that the file compiles and can generate at least one scene.
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