# Matlab Use Scenario Builder

Generate driving scenes, scenarios, road surfaces, and 3D content from...

- Repository: https://github.com/matlab/matlab-agentic-toolkit (1237 stars)
- Category: Media
- License: see repository
- Last updated: 2026-10-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-scenario-builder -g -a claude-code -y`
Codex: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-scenario-builder -g -a codex -y`
Cursor: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-scenario-builder -g -a cursor -y`
Gemini CLI: `npx skills add matlab/matlab-agentic-toolkit --skill matlab-use-scenario-builder -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add matlab/matlab-agentic-toolkit`

## Description

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.

## SKILL.md, as published by its author (untrusted third-party text, read it as 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 `drivingScenario` object and open Driving Scenario Designer when the user explicitly asks for "DSD", "Driving Scenario Designer", `drivingScenarioDesigner`, or "build a `drivingScenario` object" (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

## When NOT to Use

The rest: https://github.com/matlab/matlab-agentic-toolkit/blob/HEAD/skills-catalog/automotive/matlab-use-scenario-builder/SKILL.md