Geohash-Based High-Definition Map Provisioning System Using Smart RSU

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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Publication Details

Journal
Sensors
Published
2025-09-04
DOI
https://doi.org/10.3390/s25175509
Citations
1
Primary Topic
Automated Road and Building Extraction
Type
article
Field-Weighted Citation Impact
1.15

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article

Geohash-Based High-Definition Map Provisioning System Using Smart RSU

Chang-Joo Moon, Jimin Lee, Wangyu Park
1 citations
Sensors
Automated Road and Building Extraction
1.15
article

Geohash-Based High-Definition Map Provisioning System Using Smart RSU

Chang-Joo Moon, Jimin Lee, Wangyu Park
article en
1 citations

Abstract

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.

SensorsVol. 25(17)
Konkuk University (KR)
Ministry of Trade, Industry and Energy, Korea Institute for Advancement of Technology
Openalex Percentile: Top 19%
Automated Road and Building Extraction
1.15
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