Driving Data Importer

Driving Data Importer

This skill loads raw driving sensor data into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and provides the CLI for every preprocessing step DLA exposes (sync, crop, offset, normalize, convert timestamps). It also covers the drivingLogAnalyzer (DLA) app as an opt-in inspection tool — see Rule 0 below; DLA is never a default step.

After wrapping is done, the canonical next move is matlab-scenario-builder (trajectory smoothing, scene/scenario generation, lane localization, RoadRunner / drivingScenario / OpenSCENARIO / OpenDRIVE / OpenCRG / Unreal export).

Rule 0 — DLA is opt-in only (HARD RULE, READ FIRST)

Never call drivingLogAnalyzer unless the user explicitly asks for it or has reported a sensor-data problem DLA is built to debug. Auto-launching DLA after wrapping data is a first-attempt-success failure: it stalls the user (a UI app forces context-switch, scrub, click, confirm) and signals that the agent is not confident the import worked.

When DLA IS allowed — only these two cases:

1. Explicit user request — user types DLA, drivingLogAnalyzer, "open in DLA", "inspect / visualize / explore / replay / analyze the recording", "open the driving log analyzer".
2. Reported sensor-data problem that DLA is the right tool for:
   • "the sensors look out of sync"
   • "camera and lidar timestamps don't match"
   • "actor cuboids float above the cars" (overlay alignment)
   • "I see missing frames / a gap in the timeline"
   • "the offset looks wrong / the timeline is shifted"

When DLA is NOT allowed (defaults — go straight to matlab-scenario-builder):

• "Virtualize this data", "build a scenario from this data", "generate a scene", "export to RoadRunner / drivingScenario / OpenSCENARIO / OpenDRIVE / OpenCRG / Unreal", "simulate this drive", "I have data, do something with it".
• Anything that has a downstream simulation or scenario target.

If you ever feel an urge to add a "let me open DLA so you can verify" step after wrapping — stop. Save the wrapped objects to sandbox/<dataset>_wrapped.mat, print a short summary, and hand off.

When to Use

• User has raw driving dataset files (KITTI, nuScenes, Waymo, custom logs, ROS/ROS2 bags, .mat, .csv, .xls, video) and needs them loaded into scenariobuilder.* objects
• User says "open in DLA", "drivingLogAnalyzer", "inspect / visualize / explore / replay / analyze this dataset" (triggers DLA — Rule 0 case 1)
• User wants to map raw structs/tables/rosbag topics to GPSData, CameraData, LidarData, ActorTrackData, Trajectory, or laneData
• User wants to attach camera/lidar Mounting Location / Mounting Angles / Intrinsics / Ego Origin Height
• User asks for multi-sensor synchronization of any kind: "sync", "align sensors", "match sample rates", "resample to a common timeline", "sensor-to-sensor alignment"
• User asks for offset correction ("drag-to-align", "time offset", "shift this sensor by X seconds")
• User asks to crop / trim / extract a segment of a recording across sensors
• User asks to normalize timestamps ("common t=0", "time origin", "POSIX to seconds", "datetime to numeric")
• User wants to export sensor data to MAT, workspace, timetable, or a reproducible script
• User needs to inspect dataset structure, identify available sensor modalities, validate calibration transforms, or check for pre-computed annotations
• User needs to compute actor tracks from lidar when no annotations exist (clustering / detector / camera-based pipeline)