Open HD map service model: an interoperable high-Definition map data model for autonomous driving

• Published in: International journal of digital earth Vol. 16; no. 1; pp. 2089 - 2110
• Main Authors: Zhang, Fengyuan, Shi, Wenzhong, Chen, Min, Huang, Wei, Liu, Xintao
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 31.12.2023; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: autonomous driving; Critical infrastructure; Data integration; data interoperation; Data models; data standards; Data structures; Data systems; HD map; High definition; Interfaces; Interoperability; Navigation; Route planning; smart cities
• ISSN: 1753-8947; 1753-8955
• DOI: 10.1080/17538947.2023.2220615

With the growth in the vehicle industry, autonomous driving has become a hot topic worldwide and has attracted increasing attention from both industrial and academic sectors. Maps, as pivotal geospatial information carriers, play a vital role in route planning and navigation service. Compared with conventional maps, high-definition (HD) maps possesses higher precision, richer information, and various services and are regarded as critical infrastructure for autonomous driving. However, heterogeneous HD map data standards and models have different characteristics and advantages, and thus they rarely meet all autonomous driving requirements for different driving objectives. This research presents an interoperable map data model, the Open HD Map Service Model (OHDMSM), to provide a reference for HD map development. The designed OHDMSM, which contains three data layers and a set of corresponding interfaces, demonstrates high interoperability for HD map data fusion and application. As a proof of concept, an HD map data system is implemented with all functions following the designed data model and interfaces of OHDMSM. The design and development of OHDMSM data structures, interfaces and systems will benefit data requesting, updating, and interoperation for HD map data worldwide, which can be helpful for developing autonomous driving and intelligent transportation in the Digital Earth.