Production-grade engineering playbooks for high-definition mapping and autonomous-vehicle
spatial data pipelines — built with Python GIS tooling and validated for fleet-scale deployment.
This site exists to help AV engineers, mapping specialists, and Python GIS developers build
reproducible spatial-data pipelines: lane geometry extraction, road-network validation, sensor
fusion, simulation data generation, and quality-control automation. Every guide is grounded in
deterministic processing, strict coordinate governance, and automotive-grade safety practices.
The material focuses on the hard parts of real systems — CRS drift, alignment failures, memory
ceilings on edge compute, batch scaling, and format synchronization across OpenDRIVE and runtime
stacks. Each workflow pairs the architecture you need with the concrete Python patterns to
implement it, from streaming OpenDRIVE parsers to SLERP-based pose interpolation.
Content is organized into three pillars. Follow a pillar from its overview down to focused,
step-by-step implementation guides, or jump straight to the topic you need below.
