Matlab Use Scenario Builder
Generate driving scenes, scenarios, road surfaces, and 3D content from...
Install
npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-scenario-builder -g -a claude-code -y- Repository
- matlab/matlab-agentic-toolkit1.2k
- Category
- Media
- Updated
- 8d ago
- License
- See repository
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization, route those to matlab-import-driving-data.
Scenario Builder for MATLAB
When to Use
- User has recorded driving data (GPS/GNSS, camera, lidar, actor tracks) and needs to convert it into a simulation-ready scenario
- User asks to export trajectories or scenarios to RoadRunner, drivingScenario, ASAM OpenSCENARIO, OpenDRIVE, ASAM OpenCRG, or Unreal Engine. Default target is RoadRunner, only generate a standalone
drivingScenarioobject and open Driving Scenario Designer when the user explicitly asks for "DSD", "Driving Scenario Designer",drivingScenarioDesigner, or "build adrivingScenarioobject" (Workflow 15). - User mentions safety standards (SOTIF / ISO 21448, ISO 26262) and scenario coverage from real-world data
- User needs to extract a road surface (OpenCRG) from lidar for vehicle-dynamics or chassis testing
- User needs to add elevation to an HD map, georeference point clouds, or extract per-frame point clouds along an ego path
- User needs to localize an ego trajectory on a map using lane detections (RVLD preferred, CLRNet fallback)
- User needs to add static objects (signs, trees, poles, buildings, barriers) to a RoadRunner HD Map from cuboid detections
- User wants to augment / enhance / improve a road scene from aerial lidar, adding trees + buildings (Variant A) or improving OSM elevation / banking / gradient / height only (Variant B), see Workflow 16
- User wants to add traffic signs from recorded camera + lidar logs with pre-detected sign bounding boxes, see Workflow 17
- User needs to generate 3D mesh assets from a single camera image
- User needs to extract critical scenario events (cut-ins, hard brakes, near-misses) from recorded drives
- User needs accurate non-ego tracks via sensor fusion (
multiSensorTargetTracker) before scenario building - User mentions multi-sensor preprocessing: synchronization, alignment, offset correction, cropping, timestamp normalization
