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Abstract
ADVANCED DATABASE SYSTEMS FOR HD MAP PROCESSING IN AUTONOMOUS VEHICLES
Mohammed Sharfuddin*
ABSTRACT
The rapid advancement of autonomous driving technologies has placed high demands on the accuracy, scalability, and real-time performance of HD map systems. This thesis explores the application of advanced database technologies, specifically PostgreSQL with PostGIS and Python-based geospatial tools, to optimize the ingestion, storage, and querying of HD map data. Drawing upon real-world experience in developing HD maps used in General Motors’ Super Cruise system,this work presents a scalable database architecture designed to handle complex spatial queries, automate validation pipelines, and maintain centimeter-level precision. The implementation supports over 750,000 miles of road coverage across North America and has demonstrated its adaptability through expansion into global markets. This research contributes practical insights into building robust geospatial databases for autonomous vehicle ecosystems and highlights future directions for enhancing data analytics and real- time updates.
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