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Abstract
OPTIMIZING DATA STRUCTURES FOR REAL-TIME HD MAP PROCESSING IN AUTONOMOUS DRIVING SYSTEMS
Mohammed Sharfuddin*
ABSTRACT
High-definition (HD) maps are a foundational component in autonomous vehicle operation, offering centimeter-level precision and layered environmental data for safe navigation. However, maintaining and processing these maps in real time poses computational challenges due to the high volume and velocity of incoming sensor and map-update data. This thesis proposes a novel approach to optimizing data structures specifically for real-time HD map processing by combiningprinciples from data structure design, spatial databases, and edge computing. Drawing on professional experience in HD map validation and academic grounding in computer science, the proposed framework demonstrates improvements in memory efficiency, data retrieval speed, and system scalability for real-time applications. Index Terms—HD Maps, Real-Time Processing, Data Structures, Autonomous Vehicles, Spatial Indexing, Edge Computing.
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