Polyline — Lane Detection & Linear Feature Mapping
Lane boundary and road marking annotation using polylines — supporting HD map generation and autonomous navigation lane-keeping systems. Ongoing internal pilot on self-hosted CVAT.
The Challenge
Autonomous vehicles need to know exactly where the lanes are — not just approximately, but with centimeter-level precision. Lane detection models are trained on polyline annotations: connected sequences of points that trace lane boundaries, road markings, curb edges, and other linear features from the vehicle’s perspective. Getting the curvature right, handling intersections, and annotating faded or partially obscured markings is where human precision matters most.
This ongoing internal pilot trains our annotation team on polyline annotation for lane detection and linear feature mapping. Annotators learn to trace lane boundaries through curves, intersections, merges, and degraded road conditions — building the skill set needed for production HD mapping and ADAS annotation projects.
Technical SpecificationsAnnotation Details
Lane & Line Types
| Feature | Description |
|---|---|
| Lane boundaries | Left/right lane edges, solid and dashed |
| Road markings | Center lines, turn arrows, stop lines |
| Curb edges | Road-to-sidewalk boundaries |
| Road edges | Paved surface boundaries |
| Crosswalks | Pedestrian crossing boundaries |
| Merge/split points | Lane merge and diverge locations |
Annotation Challenges
| Challenge | Our Approach |
|---|---|
| Faded markings | Trace best estimate, flag confidence |
| Curved roads | Dense point placement on curves |
| Intersections | Individual polyline per lane through intersection |
| Occlusion | Interpolate through vehicles blocking view |
Infrastructure
| Component | Detail |
|---|---|
| Platform | CVAT v2.58.0 (self-hosted) |
| Server | Hetzner dedicated server |
| Deployment | Docker with SSL |
| Data Security | Data never leaves our server |
| Purpose | Training + portfolio building |
Export Formats
| Format | Use Case |
|---|---|
| TuSimple | Lane detection benchmark |
| CULane | Urban lane detection |
| COCO JSON | General polyline export |
| CVAT JSON | Client CVAT import |
Who This Serves
- Autonomous vehicles: Lane-keeping, lane change assist, and path planning for L2–L5 self-driving systems
- HD mapping: High-definition map generation with centimeter-accurate lane geometry for navigation and localization
- ADAS: Lane departure warning, adaptive cruise control, and highway autopilot features
- Traffic management: Road marking inventory, intersection design analysis, and traffic flow optimization
- Infrastructure inspection: Road surface condition assessment and marking degradation monitoring
- Simulation: Realistic lane geometry for driving simulators and synthetic data generation
Production-ready on demand: Our annotators are trained on polyline annotation for lane boundaries, road markings, curb edges, and complex intersection geometry. If your perception or mapping team needs lane detection training data, we can start a pilot immediately on our self-hosted CVAT infrastructure.
Need Lane Detection Annotation?
Polyline annotation for lane boundaries, road markings, and linear features. Start with a free pilot — same CVAT infrastructure, same QA pipeline, same 98.5% accuracy guarantee.