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Author	SHA1	Message	Date
RUSHIL AMBARISH KADU	2d6d04e0b0	feat: initial commit CARLA ADAS modular scenario-driven simulation pipeline ## Summary First commit of the Fox CARLA simulation pipeline. Establishes a fully working, end-to-end ADAS data collection and visualization system built on CARLA 0.9.16. --- ## What is included ### Core Pipeline - Multi-sensor synchronous simulation (Camera, Radar, LiDAR) at configurable FPS - Frame-aligned sensor data captured using CARLA synchronous mode with fixed delta time - Structured dataset output: PNG images, NPY arrays, JSONL metadata per frame - MCAP conversion script producing Foxglove-compatible topics (/camera, /lidar, /radar, /ego_pose) - Ground truth vehicle tracking embedded in every frame record ### Modular Scenario Architecture - Abstract ScenarioBase plugin interface (setup / step / cleanup lifecycle) - Dynamic scenario loader via importlib main.py never imports scenarios by name - Three implemented ADAS test scenarios: - braking : Lead vehicle hard braking (emergency stop at configurable frame) - cutin : Adjacent lane NPC forced lane change into ego lane - obstacle : Static traffic cone placed on ego lane - All NPC placement via CARLA waypoints zero hardcoded world coordinates - Scenario metadata embedded into every JSONL frame record for MCAP traceability ### Orchestrator (src/main.py) - Fully scenario-agnostic scenarios selected via --scenario CLI flag - Supports --frames override for quick test runs without editing config - Supports --list-scenarios for dry-run discovery (no CARLA server required) - Deferred CARLA import so the process works without a live server for non-simulation commands ### Configuration (config.py) - Single source of truth for all simulation, sensor, and scenario constants - Scenario trigger frames and distances fully configurable without code changes ### Recorder (src/recorder.py) - Session folders named <scenario>_YYYYMMDD_HHMMSS for easy identification - extra_meta parameter merges scenario state into every frame record automatically ### Developer Tooling - run.bat: one-click launcher that activates the carla312 conda environment - intel/context.md: comprehensive AI-agent and developer reference document - .gitignore: excludes data/, *.mcap, __pycache__, logs/, *.pyc --- ## Architecture src/main.py (orchestrator) |-- scenario_loader.py (importlib-based dynamic loader) |-- sensors.py (SensorManager: camera + radar + lidar) |-- recorder.py (per-frame data writer) scenarios/ |-- base.py (ScenarioBase ABC) |-- braking.py (BrakingScenario) |-- cutin.py (CutInScenario) |-- obstacle.py (ObstacleScenario) config.py (all constants) data_to_mcap.py (dataset -> MCAP converter) run.bat (conda env launcher) intel/context.md (codebase reference) --- ## Usage run.bat braking run.bat cutin --frames 120 run.bat obstacle python data_to_mcap.py --- ## Environment - CARLA 0.9.16 - Python conda env: carla312 (miniconda) - Key deps: carla, numpy, opencv-python, mcap --- ## Known Limitations (future work) - MCAP uses JSON encoding (functional; Protobuf migration planned) - Intersection scenario not yet implemented (requires junction-aware waypoint logic) - Single ego vehicle assumed throughout - Foxglove layout presets not yet defined	2 months ago