YING Shen, JIANG Yuewen, GU Jiangyan, LIU Zhilin, LIANG Yuanyi, GUO Chi, LIU Jingnan. High Definition Map Model for Autonomous Driving and Key Technologies[J]. Geomatics and Information Science of Wuhan University, 2024, 49(4): 506-515. DOI: 10.13203/j.whugis20230227
Citation: YING Shen, JIANG Yuewen, GU Jiangyan, LIU Zhilin, LIANG Yuanyi, GUO Chi, LIU Jingnan. High Definition Map Model for Autonomous Driving and Key Technologies[J]. Geomatics and Information Science of Wuhan University, 2024, 49(4): 506-515. DOI: 10.13203/j.whugis20230227

High Definition Map Model for Autonomous Driving and Key Technologies

  • High definition (HD) map is an indispensable part of autonomous driving, and its development will greatly affect the level of autonomous driving.The existing HD map models are diverse, lacking the systems thinking of “human-vehicle-road-map”, and the vehicle-oriented consideration is not thoughtful enough. Based on the consideration of more explicit layers, more comprehensive elements and more prominent user characteristics, we attempt to refine and enrich the data logic structure of intelligent high precision map, and elaborate the contents and functions of static data layer, road real-time information layer, vehicle dynamic information layer and user model layer in detail. We point out three key technologies, the collaborative updating mechanism of “cloud-edge-vehicle”, the intersection safety information framework, and the navigation decision-making driven by traffic event.It describes how these three key technologies support the global and local path navigation decisions and the control of autonomous vehicle. Decision supports of HD map for autonomous driving are explained from four aspects, perception, positioning, decision-making, and control.
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