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Geohash-Based High-Definition Map Provisioning System Using Smart RSU
by
Park, Wangyu
, Lee, Jimin
, Moon, Changjoo
in
Algorithms
/ Communication
/ Comparative analysis
/ Edge computing
/ Electronic data processing
/ Energy consumption
/ Energy efficiency
/ Geohash
/ Hashing (Computers)
/ HD map
/ Methods
/ Navigation
/ PostGIS
/ PostgreSQL 15
/ Roads & highways
/ Sensors
/ Smart RSU (Road Side Unit)
/ Spatial data
/ Vehicles
2025
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Geohash-Based High-Definition Map Provisioning System Using Smart RSU
by
Park, Wangyu
, Lee, Jimin
, Moon, Changjoo
in
Algorithms
/ Communication
/ Comparative analysis
/ Edge computing
/ Electronic data processing
/ Energy consumption
/ Energy efficiency
/ Geohash
/ Hashing (Computers)
/ HD map
/ Methods
/ Navigation
/ PostGIS
/ PostgreSQL 15
/ Roads & highways
/ Sensors
/ Smart RSU (Road Side Unit)
/ Spatial data
/ Vehicles
2025
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Do you wish to request the book?
Geohash-Based High-Definition Map Provisioning System Using Smart RSU
by
Park, Wangyu
, Lee, Jimin
, Moon, Changjoo
in
Algorithms
/ Communication
/ Comparative analysis
/ Edge computing
/ Electronic data processing
/ Energy consumption
/ Energy efficiency
/ Geohash
/ Hashing (Computers)
/ HD map
/ Methods
/ Navigation
/ PostGIS
/ PostgreSQL 15
/ Roads & highways
/ Sensors
/ Smart RSU (Road Side Unit)
/ Spatial data
/ Vehicles
2025
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Geohash-Based High-Definition Map Provisioning System Using Smart RSU
Journal Article
Geohash-Based High-Definition Map Provisioning System Using Smart RSU
2025
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Overview
High-definition (HD) maps are essential for safe and reliable autonomous driving, but their growing size and the need for real-time updates pose significant challenges for in-vehicle storage and communication efficiency. This study proposes a lightweight and scalable HD map provisioning system based on Geohash spatial indexing and Smart Roadside Units (Smart RSUs). The system divides HD map data into Geohash-based spatial blocks and enables vehicles to request only the map segments corresponding to their current location, reducing storage burden and communication load. To validate the system’s effectiveness, we constructed a simulation environment where multiple vehicle clients simultaneously request map data from a Smart RSU. Experimental results showed that the proposed Geohash-based approach achieved an average response time (RTT) of 1244.82 ms—approximately 296.3% faster than the conventional GPS-based spatial query method—and improved database query performance by 1072.6%. Additionally, we demonstrate the system’s scalability by adjusting Geohash levels according to road density, using finer blocks in urban areas and coarser blocks in rural areas. The hierarchical nature of Geohash also enables consistent integration of blocks with different resolutions. These results confirm that the proposed method provides an efficient and real-time HD map delivery framework suitable for dynamic and dense traffic environments.
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