High Definition Map Model for Autonomous Driving and Key Technologies

被引:0
|
作者
Ying, Shen [1 ,2 ,3 ]
Jiang, Yuewen [1 ]
Gu, Jiangyan [1 ]
Liu, Zhilin [1 ]
Liang, Yuanyi [1 ]
Guo, Chi [4 ,5 ]
Liu, Jingnan [4 ,5 ]
机构
[1] School of Resource and Environmental Sciences, Wuhan University, Wuhan,430079, China
[2] Key Laboratory of Geographic Information System, Ministry of Education, Wuhan University, Wuhan,430079, China
[3] Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan,430079, China
[4] GNSS Research Center, Wuhan University, Wuhan,430079, China
[5] Hubei Luojia Laboratory, Wuhan,430079, China
关键词
Autonomous vehicles - Decision making - Digital television - Roads and streets - Systems thinking;
D O I
10.13203/j.whugis20230227
中图分类号
学科分类号
摘要
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. © 2024 Editorial Department of Geomatics and Information Science of Wuhan University. All rights reserved.
引用
收藏
页码:506 / 515
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