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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Controls the traffic-light actors on a running CARLA server — set a light green/red/yellow/off, freeze all lights (optionally all-green), set phase timing (green/yellow/red durations), and reset to the normal cycle. Target all lights, one by id, all in a junction, or the nearest. Use when the user asks to "make the light red", "freeze all lights green", "change the light timing", "turn the traffic lights off", or "reset the lights". This is the light actors, not the Traffic Manager (that's control-traffic).
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Paths.
scripts/…andreferences/…below are relative to the directory holding this SKILL.md. Your working directory is the user's project, not that directory, so prefix them with its absolute path or the command is not found.
Drive the actual traffic.traffic_light actors: set states, freeze them, tune
phase timing. Not to be confused with control-traffic
— that is the Traffic Manager governing how autopilot vehicles drive; this is
the lights themselves.
Progress:
- [ ] Step 1: Check prerequisites (bash scripts/check_env.sh), clear FAILs
- [ ] Step 2: list to see lights/states; get a junction id from map-waypoints if needed
- [ ] Step 3: set / freeze / timing / reset (all, by id, by junction, or nearest)
Commands need CARLA_HOST/CARLA_PORT from scripts/env.sh. Negative
coordinates: use --near=-24,-57,1.
bash scripts/check_env.sh
source scripts/env.sh
python3 scripts/traffic_lights.py list # ids, states, timing
# freeze the whole grid green (classic "green wave" / free-flow test)
python3 scripts/traffic_lights.py freeze on --state green
python3 scripts/traffic_lights.py freeze off # back to normal cycling
# set one light, or all in a junction, or the nearest to a point
python3 scripts/traffic_lights.py set --state red --id 42
python3 scripts/traffic_lights.py set --state green --junction 838
python3 scripts/traffic_lights.py set --state red --near=-24,-57,1
# phase timing (seconds) on all lights
python3 scripts/traffic_lights.py timing --green 20 --yellow 3 --red 10 --all
python3 scripts/traffic_lights.py reset # normal cycle again
Example 1: let traffic flow
User says: "make all the lights green so cars don't stop"
freeze on --state green. All lights hold green until freeze off / reset.
Example 2: red light at one junction
User says: "make the crossroads in the middle red"
map-waypoints junctions --arms 4 → central junction id → set --state red --junction <id>.
Example 3: faster cycle
User says: "shorten the light cycle"
timing --green 10 --yellow 2 --red 6 --all.
Problem: lights snap back after set
Cause: they keep cycling; set changes the current state, the cycle continues.
Solution: freeze on to hold a state, or timing to change the cycle itself.
Problem: --junction returns nothing
Cause: wrong junction id, or that junction has no signalised lights.
Solution: get the id from map-waypoints junctions; not all junctions are lit.
Problem: vehicles still stop at a green I set
Cause: they may be on a different phase, or autopilot reacts to its own light.
Solution: freeze on --state green affects all; or let cars ignore lights via
control-traffic (ignore-lights).
Traffic-light state on the server (states/freeze/timing). No file. list reports
current states and timings.
Detail (states, freeze semantics, groups, per-junction/waypoint lookup) in references/traffic-lights.md.
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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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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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Summarize ScenarioRunner results to see which scenarios passed and which checks failed. Compare runs before and after changes, or analyze recorded driving to produce measurements and plots of vehicle distance and deviation from the lane center.
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Checks a local CARLA checkout for missing API documentation, outdated references, broken links, and pages absent from navigation. Produces a grouped Markdown report without building the project or running the simulator.
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Read and display CARLA object bounding boxes, then project them onto a camera image as 2D rectangles. Export an annotated PNG and box coordinates in JSON for object detection annotation work.
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Builds CARLA's ue4-dev branch on Linux, producing the Unreal Engine 4.26 editor, server modules, and an installed Python client package. Fetches required content, optionally compiles native ROS 2 support, and verifies the build against a source-built server.
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