Abstract:
Objectives The development of high definition (HD) map is of paramount importance in advancing the digital infrastructure of transportation and serves as a fundamental component in creating the “data brain” of intelligent vehicles and smart cities. Furthermore, it promotes the growth of intelligent logistics networks and traffic safety risk monitoring systems.
Methods The existing HD map models are analyzed from the perspective of map information transmission models, and the concept of constructing HD map models based on map cognition mechanisms is introduced. It also provides an overview of domestic and international standards for HD map formats. Moreover, the principles to be followed in the compilation of HD map for intelligent driving in China are outlined. Additionally, key technologies involved in HD map production and updates are explored, with a particular focus on map collection, processing, and verification. The current application status of HD map is analyzed through the examination of examples such as vehicle planning and perception.
Results The development of HD map has made significant progress, but it also encounters difficulties and challenges. Existing HD map models tend to be complex and lack sufficient representation of dynamic elements, resulting in difficulties in maintaining real-time accuracy. Additionally, the production capacity of HD map remains insufficient to meet the demands of development, and challenges related to geographic information security and limited application depth persist.
Conclusions A concept of establishing a closed-loop architecture for HD map using cognitive models is introduced. It highlights the significance of ensuring data security and promoting intelligent verification of maps and emphasizes the extensive application prospects of high-precision maps. During the research process of HD map, it is crucial to collaboratively address the difficulties and challenges, which can promote HD map to better serve intelligent transportation and societal development.
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