Review and challenge: High definition map technology for intelligent connected vehicle
Mengmeng Yang, Kun Jiang, Benny Wijaya, Tuopu Wen, Jinyu Miao, Jin Huang, Zhong Cao, Wei Zhang, Huixian Chen, Diange Yang
Abstract
An accurate and up-to-date High Definition (HD) Map is critical for an intelligent vehicle to drive safely and effectively. Although research in this area is growing, there is still a lack of clarity in defining HD maps for intelligent connected vehicles (ICVs). This gap in knowledge is particularly challenging for new researchers, who often struggle to find suitable HD map datasets due to a lack of comprehensive reviews on current HD map products, as far as the authors' knowledge. Thus, this article aims to bridge this gap by providing a thorough analysis of the core ideas of HD map technology. Initially, this paper presents the brief history of HD map. Following this, it describes the taxonomy and ontology of HD maps, complete with the HD map contents and existing standards. An insight into the mapping process is also given by discussing the algorithms used for creating and updating HD maps. This manuscript also lists current HD map products and the open-sourced dataset available for interested researchers in this space. As part of this study, the authors also describe common applications of HAD maps in ICVs. Finally, the article highlight the key research challenges and potential future directions in this field. Addressing these challenges is vital for the advancement and integration of HD maps for ICVs.