High-Definition (HD) Map Production & Dynamic Updates

Feiyan provides HD mapping services that meet stringent requirements for autonomous driving and smart navigation systems. Leveraging our proprietary AIMS Multi-sensor System, Y-1 UAVs, and satellite imagery with petabyte-scale processing capabilities, we deliver precise, up-to-date digital foundations that adhere to high-accuracy electronic highway map element specifications.

Our Differentiated Solution Framework

Built on the Swift4D Platform, our framework integrates multi-source acquisition, automated production, and dynamic updating:

Integrated Acquisition: AIMS (LiDAR + oblique) conducts wide-area base mapping; Y-1 UAVs refine ramps, toll plazas, and work zones; satellite imagery ensures full coverage.

Swift4D Processing: Automated generation of lane-level features—including lane lines, curbs, barriers, traffic signs, and poles—with 5cm relative accuracy and 10cm absolute accuracy.

SwiftAI Vectorization: Deep learning models automatically identify, vectorize, and attribute road markings, sign faces, and traffic lights, reducing manual verification by over 80%.

Dynamic Updates: Crowdsourced vehicle data and routine UAV patrols detect road changes (rerouting, repainting, new signs), enabling weekly incremental updates and version management.

Application Scenarios & Client Value

Application Scenarios

Autonomous driving HD maps (lane-level navigation and decision-making for L3+ systems)

Smart navigation & V2X (lane-level guidance, vehicle-to-everything applications)

Traffic simulation & digital twins (high-fidelity road models for driving simulators)

Road asset inventory & maintenance (precise location and status of signs, barriers, markings)

Client Value

Standard Compliance: Products align with HD map specifications for direct integration into mainstream autonomous systems.

High Efficiency: Air-space-ground integration compresses thousand-kilometer map production from months to weeks.

Freshness Assurance: Weekly dynamic updates keep map data synchronized with real road conditions, reducing decision risks from outdated information.

Cost-Effective: AI-driven vectorization minimizes field surveys and manual editing, enabling scalable commercial deployment.